{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "raw", "metadata": {}, "source": [ "Texto y c\u00f3digo sujeto bajo Creative Commons Attribution license, CC-BY-SA. (c) Original por Lorena A. Barba y Gilbert Forsyth en 2013, traducido por F.J. Navarro-Brull para CAChemE.org" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[@LorenaABarba](https://twitter.com/LorenaABarba) - \n", "[@CAChemEorg](https://twitter.com/cachemeorg)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "12 pasos para Navier-Stokes\n", "=====\n", "***" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Por un momento, recordemos las ecuaciones de Navier-Stokes para un fluido incompresible, donde $\\vec{v}$ representa el campo de velocidades:\n", "\n", "\\begin{eqnarray}\n", "\\nabla \\cdot\\vec{v} &=& 0\\\\\\\n", "\\frac{\\partial \\vec{v}}{\\partial t}+(\\vec{v}\\cdot\\nabla)\\vec{v} &=& -\\frac{1}{\\rho}\\nabla p + \\nu \\nabla^2\\vec{v}\n", "\\end{eqnarray}\n", "\n", "La primera ecuaci\u00f3n representa la conservaci\u00f3n de la masa manteniendo la densidad constante. La segunda ecuaci\u00f3n es la conservaci\u00f3n del momento. Sin embargo, aparece un problema: la ecuaci\u00f3n de continuidad para el flujo incompresible no tiene una variable dominante y no hay manera obvia para acoplar la velocidad y la presi\u00f3n. En el caso de flujo compresible, por contra, la continuidad de la masa proporcionar\u00eda una ecuaci\u00f3n con la evoluci\u00f3n de la densidad $\\rho$, que est\u00e1 acoplada con una ecuaci\u00f3n de estado que relaciona $\\rho$ y $p$.\n", "\n", "En flujo incompresible, la ecuaci\u00f3n de continuidad $\\nabla \\cdot\\vec{v}=0$ proporciona una *restricci\u00f3n cinem\u00e1tica* que requiere que el campo de presi\u00f3n evolucione de manera que la tasa de expansi\u00f3n $\\nabla \\cdot\\vec{v}$ deber\u00eda desaparecer en todas partes. Una forma de salir de esta dificultad es *construir* un campo de presi\u00f3n que garantice que la continuidad se satisface, tal relaci\u00f3n se puede obtener mediante la adopci\u00f3n de la divergencia de la ecuaci\u00f3n de momento. En este proceso, \u00a1una ecuaci\u00f3n de Poisson para la presi\u00f3n aparece!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Paso 10: La ecuaci\u00f3n de Poisson en 2D\n", "----\n", "***" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "La ecuaci\u00f3n de Poisson se obtiene a\u00f1adiendo un t\u00e9rmino fuente (*source term*) a la derecha de la ecuaci\u00f3n de Laplace:\n", "\n", "$$\\frac{\\partial ^2 p}{\\partial x^2} + \\frac{\\partial ^2 p}{\\partial y^2} = b$$\n", "\n", "As\u00ed, a diferencia de la ecuaci\u00f3n de Laplace, hay algo de valor finito en el interior del campo que afecta a la soluci\u00f3n. La ecuaci\u00f3n de Poisson act\u00faa para \"relajar\" las fuentes iniciales en el campo.\n", "\n", "En forma de datos discretos, esto se ve casi igual que en el [Paso 9](http://nbviewer.ipython.org/urls/bitbucket.org/franktoffel/cfd-python-class-es/raw/master/lecciones/12%2520-%2520Paso%25209.ipynb), a excepci\u00f3n del t\u00e9rmino de fuente:\n", "\n", "$$\\frac{p_{i+1,j}^{n}-2p_{i,j}^{n}+p_{i-1,j}^{n}}{\\Delta x^2}+\\frac{p_{i,j+1}^{n}-2 p_{i,j}^{n}+p_{i,j-1}^{n}}{\\Delta y^2}=b_{i,j}^{n}$$\n", "\n", "Al igual que antes, lo reorganizamos para obterner una ecuaci\u00f3n para $p$ en el punto $i,j$. Por lo tanto, obtenemos:\n", "\n", "$$p_{i,j}^{n}=\\frac{(p_{i+1,j}^{n}+p_{i-1,j}^{n})\\Delta y^2+(p_{i,j+1}^{n}+p_{i,j-1}^{n})\\Delta x^2-b_{i,j}^{n}\\Delta x^2\\Delta y^2}{2(\\Delta x^2+\\Delta y^2)}$$\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Vamos a resolver esta ecuaci\u00f3n, suponiendo un estado inicial de $p=0$ en todas partes, y aplicando las siguientes condiciones de contorno:\n", "\n", "$p=0$ en $x=0, \\ 2$ y $y=0, \\ 1$\n", "\n", "y el t\u00e9rmino fuente se compone de dos picos iniciales en el interior del dominio, de la siguiente manera:\n", "\n", "$b_{i,j}=100$ en $i=nx/4, j=ny/4$\n", "\n", "$b_{i,j}=-100$ en $i=nx*3/4, j=3/4 ny$\n", "\n", "$b_{i,j}=0$ en el resto de puntos.\n", "\n", "Las iteraciones avanzar\u00e1n en pseudo-tiempo para relajar los picos iniciales. La relajaci\u00f3n bajo la ecuaci\u00f3n de Poisson se vuelve m\u00e1s y m\u00e1s lenta a medida que evolucionan. *\u00bfPor qu\u00e9?*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Echemos un vistazo a una posible manera de escribir el c\u00f3digo de la ecuaci\u00f3n de Poisson. Como siempre, cargamos nuestras librer\u00edas Python favoritas. Tambi\u00e9n queremos hacer algunas figuras preciosas en 3D. Obtengamos nuestros par\u00e1metros que hemos definidos y la inicializaci\u00f3n. \u00bfQu\u00e9 notas del planteamiento propuesto a continuaci\u00f3n?" ] }, { "cell_type": "code", "collapsed": false, "input": [ "%pylab inline\n", "from mpl_toolkits.mplot3d import Axes3D\n", "from matplotlib import cm\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "# Par\u00e1metros\n", "nx = 50\n", "ny = 50\n", "nt = 100\n", "xmin = 0.\n", "xmax = 2.\n", "ymin = 0.\n", "ymax = 1.\n", "\n", "dx = (xmax-xmin)/(nx-1)\n", "dy = (ymax-ymin)/(ny-1)\n", "\n", "# Inicializaci\u00f3n\n", "p = np.zeros((nx,ny))\n", "pd = np.zeros((nx,ny))\n", "b = np.zeros((nx,ny))\n", "x = np.linspace(xmin,xmax,nx)\n", "y = np.linspace(xmin,xmax,ny)\n", "\n", "# Fuente\n", "b[nx/4][ny/4] = 100\n", "b[3*nx/4][3*ny/4] = -100\n" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] } ], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Con esto, estamos listos para avanzar en la estimaci\u00f3n inicial de pseudo-tiempo. \u00bfC\u00f3mo es el c\u00f3digo de abajo diferente de la funci\u00f3n que se utiliza en el [Paso 9](http://nbviewer.ipython.org/urls/bitbucket.org/cfdpython/cfd-python-class/raw/master/lessons/12%2520-%2520Step%25209.ipynb) para resolver la ecuaci\u00f3n de Laplace?\n" ] }, { "cell_type": "code", "collapsed": false, "input": [ "for it in range(nt):\n", "\n", " pd[:][:]=p[:][:]\n", "\n", " p[1:nx-1,1:ny-1] = ( dy**2/(2*(dx**2+dy**2))*(pd[2:nx,1:ny-1]+pd[0:nx-2,1:ny-1]) +\n", " \t\t dx**2/(2*(dx**2+dy**2))*(pd[1:nx-1,2:ny]+pd[1:nx-1,0:ny-2]) -\n", "\t\t\tb[1:nx-1,1:ny-1]*dx**2*dy**2/(2*(dx**2+dy**2)) )\n", "\n", " p[0,:] = p[nx-1,:] = p[:,0] = p[:,ny-1] = 0.0" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Tal vez podr\u00edamos reutilizar el la funcion de representar del [Paso 9](http://nbviewer.ipython.org/urls/bitbucket.org/cfdpython/cfd-python-class/raw/master/lessons/12%2520-%2520Step%25209.ipynb), \u00bfno te parece?" ] }, { "cell_type": "code", "collapsed": false, "input": [ "def plot2D(x, y, p):\n", " fig = plt.figure(figsize=(11,7), dpi=100)\n", " ax = fig.gca(projection='3d')\n", " X,Y = np.meshgrid(x,y)\n", " surf = ax.plot_surface( X,Y,p[:], rstride=1, cstride=1, cmap=cm.coolwarm,\n", " linewidth=0, antialiased=False )\n", " ax.set_xlim(0,2)\n", " ax.set_ylim(0,1)\n", " ax.view_init(30,225)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "plot2D(x, y, p)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAnQAAAGUCAYAAAC8xb/QAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsvXusJPlV5/mNyHdm3aq6t7qrul3ldWN3g3tY8CC310IW\nY3tM2yMELa80awwrbc9gexCsByEM3UYg1iy0p9sI/hkPiNk1pi2BsZHHbmMbQzfa9ayR3I0Y81oW\naNu0qX5U9aPuM1+RGRH7R94T+Ytf/n4Rv3hlRkSej1SqqryRkZEZeTM+ec7vnGP5vu+DYRiGYRiG\nqSz2pg+AYRiGYRiGyQYLHcMwDMMwTMVhoWMYhmEYhqk4LHQMwzAMwzAVh4WOYRiGYRim4rDQMQzD\nMAzDVBwWOoZhGIZhmIrDQscwDMMwDFNxWOgYhmEYhmEqDgsdwzAMwzBMxWGhYxiGYRiGqTgsdAzD\nMAzDMBWHhY5hGIZhGKbisNAxDMMwDMNUHBY6hmEYhmGYisNCxzAMwzAMU3FY6BiGYRiGYSoOCx3D\nMAzDMEzFYaFjGIZhGIapOCx0DMMwDMMwFYeFjmEYhmEYpuKw0DEMwzAMw1QcFjqGYRiGYZiKw0LH\nMAzDMAxTcVjoGIZhGIZhKg4LHcMwDMMwTMVhoWMYhmEYhqk4LHQMwzAMwzAVp7npA2AYhlk3vu/D\n8zzM53PMZjPM53P0+33Yto1GowEAsCxrw0fJMAxjDgsdwzBbged5cF0Xk8kEruuGfua6bvBnNpvB\n933Yto1WqwXbtlnuGIYpPSx0DMPUEt/34bpuEIUjiZtMJuh2u0EkjrazbTv4v+M4QdQOQBC5I7lj\nwWMYpmyw0DEMUwtUaVTCsiytjPm+D9/3Q9uK96Gfz2az0O0keSx3DMOUARY6hmEqC6VRZ7NZkCoF\nwgKnggSNIngAcHBwgFarhVarpRU8uq+YnrUsC41GI5A7FjyGYTaB5YufXAzDMCVGl0YFECtwooQB\nQKPRQLPZhG3bmM/n6PV6gRjO53NYloVut4tWq6WNxNHHp/gxyulZhmE2AQsdwzClRUyj0h9KgUYJ\nE20zn88DkbNtG81mE7PZDJ1OB81mM9h2NpvhzJkzwf3H4zHm83kge57nBdE7KpTQHa/4N0XvKEXL\ncscwTFFwypVhmFJBIkaRMtd1A3GjVGrU/UjggEUUrtVqodvtBjJF0bco6HEGgwEAhKKCo9EoqIBt\ntVpoNpsraVkxPSuv5eP0LMMwRcBCxzDMRolLo0alOyl657ouPM8LZKndbucqTLTfTqcTHO9sNgsi\nec1mMxA88XjFY6CoHUUaxefH6VmGYbLCQscwzFoR06EUhRPTqFGpSSqCIIkjIWq322urOLUsC81m\nE81mE71eL1RZe3JyAt/3lelZVfROrp7l9CzDMGlhoWMYpnBI4Eh8PM+D7/uhFiC6+1EKlaJaVMzQ\n6XS091sntm2j3W6j3W4HUcPZbAbHcTKlZ+XWKCx4DMNEwULHMEzuiOlQx3FCadSoliJ0P3FyA6U7\nu91u6SNX4hq5brcbikSORiN4nreSnhXvK0fvSIJF8eX0LMMwKljoGIbJhbQ94USBI3kh6RGLGaqI\nZVmBvAEIone0/k78ObVQofuJf4uRSrqd07MMw4iw0DFr4S//1b8AALzmi/91w0fC5IVYzOA4DjzP\nC35mmkalYoZmsxmshStDGrUobNtGp9NZKa6YTCapiivE/XJ6lmG2GxY6hmGMMB2tpbufKHHUE47W\nwW2jgMjFFWJ6djgcanvf6Yor5vN5EPWj15VHkzHM9sBCxzCMliyjtUx6wjFLotKzYnEFRfFUxRXU\ns081mozTswxTb1jomLXyl//qX3DatcTE9YSLSqOuqyfcthCVnj05OdGmZ+m+gD49y73vGKZ+sNAx\nzBYjV6M6jhNUXpoWM8g94bY5jVoUqvQsRe/E3neUphXvJ/6t630n/s0wTDVhoWMK50+/67U4c2mw\n6cNgThHTqDSnFECQpmu328r7VaEn3LZgWVbQ+w5AKHo3Ho/hOE7i3ndiepaLKximerDQMYXDMrdZ\nTEZriduJ9xOjcGIatQo94bYJOi9iwYmu95143ng0GcPUBxY6Zu3wOrpiyTJai9JxJHGbGK3FZCPP\n3nc8moxhqgMLHcPUAFng0o7Wov9vQ0+4OkLnXERXXDGdTiOLK3g0GcNUCxY6hqkg4sxQXTVq0p5w\n7XYbs9kM3W53nU+FWSNicQUQ/iIg9r4jyTMdTQZgJXrHgscw64WFjikUXUHEX7z1e/DP//j/2cAR\nVRe5qW+SNKpJTzhRCpntIEl6Vtf7Dgh/UaDbOT3LMOuFhY7ZCJbNH/BxiOmx2WyWKI3KPeGYNKTt\nfSf+zaPJGGYzsNAxTElIO1oL4J5wzALVGrq0mPa+SzKabD6fh76QcHqWYfKDhY4pFG5ZEk2W0Vqi\nwAHLnnA8WospAl3vO8dxQqPJTHrfiel/Ts8yTD6w0DGF8fnWt+HKWy5pf76N6+hEEXMcJ2jqC5iN\n1lL1hJN7izHMOhB7EorFFaPRCK7rrkTv4nrfTafTIOXL6VmGSQ4LHVMY5//7M5E/34Z1dHmkUdfV\nE05c/8QwSYgqrphMJgAQ2/uOvtzo0rPcB5FhomGhY5icyZpGpT/U4Z97wjGm5LmGLgtycQUJntz7\njtboydE7VXqWR5MxTDQsdAyTkbjRWiZpVLknHBczMHVBlDBVepa+uHiet/K7wqPJGMYcFjpmo1Rx\nHZ2YRqU/SaJwJj3hGKau6NKz4/EY4/EY0+nUuPcdjyZjmCUsdEwh6BoKy1RlHZ1qtBawjCAk7QlH\nkxk4jcpsO5SedRwHvV4PjUYjce87YHU0GadnmW2DhY5hFFAa1XGckMAB8aO15ChcVXrCcVFE9an6\n+Uvb+47uy+lZZpthoaso3/j615W3v/JVr1rzkWSnDGlXUcTE0VqO48C27WDCgu6+3BOuesip8/F4\nvDK/tIpU9f2mKujIs/cdp2eZusNCVxF0Ahe3XRUEb1NpV7E9gm60lurbPPeEqy50jh3HCUVPbduG\n53k4OTkBsIz2lKVqlFmgK64Yj8eYz+eRve/Ev+X0LI8mY+oAC12JMZU4032UWe7WEaUTIzJ0QacL\ndtl6wjH5oFrDCCzXbdm2HURuBoNBsP1oNMJ8Psf+/r52DReTL0nlWVVcQYIX1fuO7qsbTQZgJXrH\n55ypAix0JSIPgTPdf5Fy96ff9Vrc8X3fgef+/BuFPYYpefSE8zwPjuNsTU+4qkel4ubajsfjlQs8\nQak4ivD0+33jNVzMZqGlEe12W9v7Tux/FxW9o/cQ3c7pWaYKsNBtkKIFLsljFyF4t772lYmkLo8o\nXR6jtegPRWOoL1zdP8ir+vx0DZnFfn5piVrDNRwOSxe9q7qM54Vp7zvx3In3pb/F4gqC07NMWWGh\nWzOblLgoNp2atWwLvpe8Qi+v0Vr0bZw+5KmYgRoF84d2uVBF4dbRkFklCY7jcPQuB4qU0ajRZOPx\nOPRzk953utFk4rYMs24sv+p17iWnrAJnSlK5o3SriGmUjoQuLkoXlUaN+sasiuRQNSqlVGRI6Lrd\nrtFzqDonJycYDAaluyiJ505c50TnL8nxjkYjdDqd4AJMa+jOnFnOHp5MJnBdF4NBfC9FQnxPzmaz\nID2/zujdwcEBdnZ2Klmpu6ljp/cWnbf5fG4ceSXBA5ZRvG63y+lZZiNwhC5nqi5wMmWoms0yWquq\nPeEYhIoZxCgcXTDLdu50Kb7hcAjP8zh6F8Om0sV59b4T0/0E975j1gkLXUbqJnBxRKVm//S7Xqu8\nT5q1dN/xh/93qjRq3j3huNnu+tBF4arYz09O8Zn2T8sKr6HLTtred3RfEj5V7zt5/R3D5AkLXQq2\nTeJ05L3uTlxHd3x8vLjNQOB0PeGoGTB/cJqzzt5rughqGaJweb8GcQv0OXpXXhlVnTtqRC32vqP3\nL6Faf0fv89lsxqPJmNxhoTOABS4eis7J6+eIpFG66X/49+j//K8rf6ZrS1FETziO0OWLLoIqFqLU\nnagF+kVG75jsiOeu1+uFCrIcxwk+L2gNHo8mY9YJC50CFrjN89xXnwLF/KJScVnbUjDFomsHw1M1\nllCT406nE9leo879D8XCpioh976jlCq1taH3OY8mY9YBCx1Y4LLy3L9+h9F2SaN0o1/+cVjv+9WQ\nBGw6FcfEw1G49MS114iL3pU1bbktUMFVlt53AI8mY9KxtUJXJ4mzEE4J+kj+yy7vI81+dOnWRMch\nrKN77qtP4dZffR8GP/efNvYBxinXeHgdY3HI0TtafxUnCFWjDiIqP4e0ve/ovjyajEnK1ghdnQUu\n7ucqMYvbh7yNbh/P/usfjN1PVvjDan2YCqxczAAsmjLzbNvikNtrqAQBWPROlAWBKZ44KdXJ+WQy\nCUaTqXrf8WgyxpTaCt02CZzJ/S1/OQLLt5Kvw4nbx7e86VuN9pM07frcV5/Crb/849oCCWY9xEXh\n6rq2q8yoBOHo6Ajj8RgnJyeh6E/Zo3d1iNAlIWvvO/FvTs8yRK2Eri4Sl1XgAITkK+pnUXIXt49n\n/qcfArCQuXOvfiWG//RMiiM1Y7QhqdvmlCtH4aoDRWkA4OzZsyFBiEvvMfmQRUp1ve9MKp+j0rNi\n7ztOz9afSo/+YoET9hEhX0mOw3TdXPs//W+h/ycVurgonTzX9dbvug0AMPx3H8DNFy8aP05WfN/H\ncDgMjYWqK77vYzQaodFowPM8o9FoVcRk9Nd4PIbv++j3+5s6zMT4vo/9/X3s7e2t3K4abUVjycqQ\nppvP5zg5OcH58+c3ehxZKGp0mer8iXJnOpoM4PRs3alUhK4sApdHAUHmNGpOAhd3m+p5qWQOAAb/\n3eVCo3QAMPjPH8AL/+4Dwf/XJXd1TQmJLUXEtA1H4eqDau0dVV+WKXrH7zU1UedvMpkYjyaTZ84C\nnJ6tG6UWujILXNQ2aYsQIvefUeDSPr54P9t3cdNX/gv2hZ+fveMVoe1NpU63lu6OH/re5X98H//w\nu48BAHbuvB3H/9/XAAAX/+j/wPNvew8A4IXnnw8d500XL8U/qQTU7QOO1sJRKlWMwrXbbUyn0+Di\nwdQTsXdav983XpzPRLOuL31y7zsqjokbTabrfadKz/J5ryalS7mWReKAfFKhWbB9d+U200ig6r4r\n+4pYP9fwZivb3PSV/4L9//b/AgiLnKVIMZhInSx0IZkLDjJ8DkjqBq+4jJfe+m/hWfr0Rl5yd3Jy\ngsFgUNkPODkKRx/YzWZzJe0yHo+DC0FdqWvK1fM8HBwcrKRckyCuvaMmt+uI3lG08OzZs4Xsfx3c\nuHEDu7u7G/2cEHvfzWazRK1tKLU7HA6xs7PD6dkKsvFP7TIJnIwoT+uQOxMJ06VETe67si8h6tfw\n5+rI4uk2Fx7/jLHMAWaROjFKp5S5CIbffAYX/vijeOmt/zZ0uyh4Lz5/Pfh3Frlb53zTPFBF4Wit\nDVek1pus71Fxcb4Y/eHoXTRliYtk7X0HhCONcnqWR5OVm7ULXZkFLgpZdvIQvDQSFndf0whew5+v\n3KZ7Thf+9v/C/PgEwGqKNSu3vvaVOPud/wzeZKLewLJCUbqdO2+H3evh8L/9NZoX9nDhjz+K/bv/\nl0DkbN8NiaprLz7YRLkD8k/NbhrdfFsajcYfvkxSxOHxNPlA1Vqj3W4H0d60VOkLUxRlew5Je98B\n4XV3caPJxL+ZzbOWlGtVJU4mq8RlEbgs9294q/IWhX/6y9l0HZz7+z/F/NlnldvponMicVG6s9/5\nzwBAL3TAStoVAOxeb/mf3gDzp6/i8Hv/5+Am11r9rkJyJxMnd3KKrgyI823lKFyWilROuS6oasr1\n8PAQu7u7a3k8sfJyNptlit45joPpdIqdnZ0Cj7g41v3a5wG97ylFS+tpPc/D2bNnIz9DdNWzXFyx\nWQr51K6LwAGblbh1CRwAtNywUO38w1cAQCtzpkSlXknmAMDudo2jdCuMh2heeTku/N1/BTpdvPQt\n/8NKBNK1msG6wOA2RfSuzJE7VRSu2WzmGoXb5r57VWfd502O3s3ncziOE9sYV0VdInRVQu5953ke\nxuMxXNfF4eFhot53AEKjyTg9uxlyEToWuCWbELim6xhv61s2WvOx9uc71/4eOD6I3Y9JdI4wrXyN\nlDoJbzwOR+mI6QQXvvnn8Po7ONldpIfnjTaavixzTTS98Os2t9ulSs2KUThxhmOz2eQh9xmo8+u2\nyZYj4totit45joPhcBis36zr2rs6CCl9QfR9H4PBIDiH4/E46F1oOppMlZ7l4oriSSV0LHBLNpFG\nTSJwACIFjhi88A1Yhy+FbouKzjVuvgj3heeNj0GWOjE6J6KVOkWULiR14yHQGwT/tgGcHf0N4PsY\nX3olZq1BcL95o70SxZQFb24vvrWS4I1Ojtcid2IxgxiF63a7/GHIVAZV9G42m2E4HMLzvJXoXdWF\nqOrHT9DziOp9x6PJyoux0LHELSl7FM5E4NrTo8W2Ry/Cb7bDMtffwfxrfx9+/JtvXv6nsXjbJJW6\ns9/9+sU/hsfG9wlhkHoVpQ69AWBZ6Bw9j974BN7gLNzOAPNWD/NmN7jbvNEJvb7zRnsleudaTbx0\n/bng/xcu3ZruOUhwFI6pO1HRO+qbRhf2qopRVY9bRvc8xN53gPocphlNBmAleleH13FTRBZF1EXi\n1tHUV/cY6xA4IF7iSOBw2leudfg8/GYb9ktLSUH/dEHy4Q39jhqKYgMDqWtcvhK+IUbqtKnXuAIJ\nYCl10r+97gC2IHYAMG8t7isLnsi80Q79X1VwYSp44geaHIUT15xsislkgkajEVx864hc+FGXogjX\ndXF8fFyp8Vn0u0BrtwAkWntXFurQRw9YFAxZloWeajmLhqy978S/OT2bjdqWsq17MoPYLkTVEsSE\n3KNwzsnyP5YdSByApcz1paqyKJnT0Lh5MX4rSbQOg51IqUudegXUkToA9mQIr3cG8Dzg9Px2Tl6E\n2xmgORsHchfFvNFWFlxERe8oCkcSByCQprJF4bgoorpUMUpE0Ttao9Xtdo0jP2Wiiq+9Ct/3E0t0\nkt53cnsbMT3Lo8myUxuh2/RoLTESp+sFJx+jvI5LN7mBji2JxPmwguNoDRfDukjmvFYHzaOXksuc\nIjoX+rEmBbsSnSNipC4TUVLXHaAxGQIA3O4gkDvLc9GQpHre7KLpTrUPIwueLHf9s+fhum6wpqgs\nw9CZVdEejUa1b9lSZmj0lNg3jSI/o9EoFPkpW4PsOgld1ucR1fsuTXGFbjSZuC2zoLKfXHk09s0i\ncWlSqT4sNKXWGXGIEqcTvvZ0KUWiTJLIea1lCrF59BLssRC5IzLKXLCZJHVamTMgU5RORpI6ACti\n15gvHsvylueWzrPtzlbkTrX2Tpa70VG4YjivtXdMOjzPg+d5cBwn6LslXiBIHOjCQf9mikUlEnGR\nn6pE76pE3mIqF1eYFMiI9xX/Ftcbz2YzTs8qqPwauiRil2cULglJJU6VerWkxyaJ8+1V0WpOjtT7\nPQpXsXrdsOBEQr8sx4fx22KRfm3c/m0LkYojw3o667ZvDd9kh9dr+M0mGi8K6wTF9XVYvgbAabRO\nwBXW1bmtbvhn9nJdnbzGbvHz8HmZ26vblLHn3XQ6DfpT1QFV0QkANJtNtNvtINUjrqHzPA/D4RCu\n68L3/SCyWvaWG/P5HMPhEOfOndv0oSQm6dotOq+O4yRet1UEk8kErutiMBjEb1xijo6O0Ov11raG\nVpT02WwWSDqdS93vmrz2DuDed0ANhE7GRPBMxS5LNavJOjpLeOlN18+F1sVJ6ETOdvS93RLJHGEi\ndeeEjukZpU4UOusVd8TuSiV1K/tsLqKWrcMXQlIHhMVOlDogWuyA6stdHYRO14CZPuwnk4lxUUSv\n1wsa5s5ms9C4qyKH1aehygvzqVddt9uN31iBLAb0Hl5X9K6KRTQqDg8PMRgMNrLsQEzP0gQL0+kj\nquIKStFuU/S2sinXLMipS1HwRCGM2k6FvI4uTi7FyQV+xBuuMw3LjielP1vT03VzzdWLcGOkljwg\npcwBwM5pBEAnduek8Te9QbzURayns7td+JdeHnOgSyzPDUmdNZ+vSJ09n8JrdjA7t2zHIr9+bqON\npnOakj0Vu8ZsIZckdo3T9iYkdnIKdrGNkIYteUPjKhZF0BB5EjiK1ohTNNKia7khz8KkNV3bcuEo\nG7p1W9QUV0zrlWmEX9nY5FpAVXpWNTvYND17cnISzLPeltFktRC6zAURhveXBU8eJbWyvaI4ohWx\nwH5l29P1c7LABT+f6qN1USIHZJA5EZXYyTJHpJQ679bblofjmUdMVVIHhKN1JHXLbZyQ1DVcB/O2\nlKJthFMRcoRucdviMegLgBiho9s8a3ls4vuoauPINoXc+oU+sPMcg6ZCN6z++HjxvhUvOHW9aBRB\nniKhaoqrq7rM6zxxUUT+yKPJkva+AxD6LKDiCpL/OlJJocujojXtPkJRuJiqVKIZisRFRwua8/jR\nV1EiB6zKnLw2rDGbwBuchT2MkL4kv9Q75xZSp5M5IoHUiSJH+HYjk9QBq9E6ldQBy2gdVb26p9E2\n212cSxI7OUK3uG1+elsz9H/xNvF9xHIXD0XhKJVKBQ20Fm4ThQviBUeu5js5OeGoUEmIqrqUz1Pa\nLwNp2n2UkTJH53XTR+QKaHn6iBy9q3MVe2WeWd5tSeToWdT+k66l8y07dBH3rEbsPlQiJ17oAaA5\nW0TsXMU6LQBo0M+7+oW5lDIEAG8QvdbGHpm3FPEuLapZYyN/YisRHYMd7Y/WIXWLbVajdeLrrhM7\nYCl3stiJt4m3p5U7oN6Cp+rfRwJXtuKEuKjQOioyyxRdScq6jj1qpFVR0buqIK4/Kzsmve+ooEnX\n+66OVELo0spckqpWWfDSNgeWe8sRspwB5oUQJHKRj2u0jdnge8I77VMXJ3ae0M/O6w7M0rmKaJ27\nF5YTa65+LYuSOgCxKVgAkWIHrEbtVBIn3u7azSByK77XxfeMTvrqFr2TZ9nSt3KqSK3Kh7EqKkSp\noqhWDcx6EUda9ft97RpJk0X5VXlvxlHF5yH/vnmeh6Ojo+BciuexzlNwKiF0omyZyl2aFiVxzYFN\nxnuJxQ2WJnytEjnPXn2TNd2FgHmKYgcAsOdOISK3cmwRYufJzYmRTupkmQMW693WKXVAfAoWUIud\ndypqKnFX3iau74MftKUxkbii5W6daRfdLNsyTtFIixgVApbRBHEtEFVkli3yuC7KIERxi/IB/RrJ\nMhx/VurwHIDl+DAA2NnZgWVZod53aSupq0AlhE7ENFUqrlWLkju5qjVqW/Gxbd+NlUtR7nSROxUk\ncnFYvreSKpSxvXkwt7QxNZCsCGSxU8lcsK1hjzuVyIkULXWz3vlgvq2IZ69KmHzfxXaSEEaIWei2\n0+OWH0e1rcntQHjG7AvPhyd23Hzx4sqxq1jHB7qurUi3292KSlHdNASxkq/dbq+kipj1Iq+RJBFX\nRe88z6v8+7YuQkeIa+jEyFydf6cqJ3RA8hSsXIgQtZ4tqlWJfD+TKJ5K5FSyAGBl7JQO04ibLT02\niV1oXykkL0rkVraNiNbNdi4E/6aUp4o8pM45K7QnkQWOzrFwu0q46HFEsaPXOKvYyY+li8KFDlt6\n/0XdRxQ8U7nLi6i2InWJwqVFvNiIKb/pdJq4LUqVL8hlP3ax7YVc4XxycgLP8zCZTOD7fmVFvOzn\nIAm6LEOVlm2koRJCt8mCiCQRPNq3LWxjUhAhi5yrSL+qttMhi1wUouSZyp3bXnZzbzjxKV+V1Iky\nByzWruUpdaLAyVi+p6429r2VaJ3tuSsCXoTY0WMBwKxhVlIfem+WTO7EtiLUKmAdbUWqDrdFqQZy\nS42DgwPYtr0i4lVKo9dN6OoubypKK3R5S1wUSQoioiN46sfURVjEOa1xiDLnRqRZW076tKqJ3Iky\nJ/4/TuwoBStPWghtk1HqZmf2Io9BhM6bMlqnkDpgNbKqSuFGiZ34PhAnSiSRMd1xx8kdbS//TE7N\nnt+NaT2joYxtRarONrVFKXO7DFO63S4ajUaihrhloo5Ct22URuiyClywn5TzWqMKIswjeKf9bmI+\nnKgdhXzRD45FiLCZR+UWxy+PqgIQDJ1PgmrdnSxzoe3bvVipm/cWbVKo0EAFrQnUiZ0sdc7OTaGf\nJz3/ymidIgULmEfrFtvOMWv2lGn5lWMwiLTpxA6I7m2YRPwA4GB/HwBwfHQUG72rUluRqmPSFoV6\nb1X1YlbFY1YR1RB3OByWNnpX1feNCt2axro8Px2lETq6uGQVO9NiiCSPpRK86HV4q28a0xYlwEL0\nSOqokjJK7OyYNWSi5CWVOxI7t9GOva8uWkciR/jNdqTUAdHROr/ZXBQzqH5mkBaXSZqCBZbRulkr\nPLtRJ1AroqaL+um210Tt5Mdbea9GiJ/8/o+K3pHc1aWtSNVRtUUZjUZwXRcHBweViAjViSgZ0jXE\nHQ6HpWphUyehq0uj56SURuiINC1KtPtSpEezVMWa9AiTCS7cirSr6n669W+qZsItg5YlK/uRInix\nkiY8rtvsGgmhKHayzBHUBiQuWidL3awvpVUV5yro6ZZA7OJSsE77jOJe5vvJQ+zk95BKQnWPIx6b\n6r5xkUQ5Nbu7t7f1BQ1lgaJ37XYbruui1+tVri1K1WXC9Ph1s4FNxlkVTdXPgYjuudTl+ekondCJ\n5BW1C13IDIRRlru4x1+Z6GAYjTOVQhW278JV9KdrxES+ZIKh8wpRU0lk1Pah7Vp9uK0+7Lh5tzHR\nOpK6FZEjLFspdUD6aJ3TXZVQCx58KATK95UR2axiJ7YgiTpWImlqVcQkLSyzf+NG8O91V80y0XBb\nlPWSZf1f3DirdUbvtkHo6k4phS6P9XQmF3Kd3KWtig3WOynakujSorLIrSymlyJ2ceInS56p4Mlp\nWd14MXl7pQgKaUhqmBwldlHRupkgV9rUckapczpSGxbfh2qWrYVTSYMc+T2VtJRiN1e81hb8RKIV\nJ3e0r6it41EMAAAgAElEQVSoHh1PUjbZEoWJxrQtyqajd3W4AGc9ft04q3VF7+qUpuQIXYlIm3ZN\nWxCx8vgJGgwDZmPCZMkzjuKdCl5QaJEgkufDwlyoiG1GVJAGj9dowmss0ou2gQyKYudK68lC+7Vb\niaJ1M0WUzLMb0VIHGKdgVyRu5U6nr3eOYudbNuaKljS6NXxR6dPIQ4/YPq6YIk+5A1jwykZULzWA\n26KkoSgZ1UVa5WH0eVWR10GqiTo9lySUUuhEkshd0rVTUfuLak8i3zeqe3/odk/fjkJ3H7liluaD\nEuJQeEJ3ISa5U4md11h9K9DIMROxc06LFKIigibROqe/aJuhaxZMYpwmWud0zy5FzZQYsdOlYQFg\npmgvo5M07Rq+iPsEh6hpSRJHljV1pnD0bn0kvYiVpS1KlYbCb4q4YfR5RO/q0DqGIOGVqft7rPRC\nJ+LDMorYmVa6JpVF2lcRa+rk+5iOChMFLy4CRshRO5XMhY4tQuzkvnJusx2b5lWJ3awdnmIRNwEi\nNlp3eq5mHamYgX6hcxI7MVqnEjgdcWIH6NO0ur6GaSN6MnnJnAzLXXmJa4tC8reJxfplZxPRIFWV\nM6VmxehdUhmvy3mtU/o4CZUQuixr6kwXxuvWyanum3VNXVybEQBwpbV0JoLnSem82BSnZWPWEqY+\nxGwvil1Ug2Bax2cidqrCjuD4Tl+3pNE6sSKVhGsFy0oudUBofd2sEX4NdAUSUcRVpeqmhpjsU7df\nQB0JTHL/rHBqttyohEFO95HgZb1wVj09tunjF2UcWI3emcr4pp9HntTpuSShEkKXZk1dnuvp4vYn\nHl+a9XRJBc80eheV4lRd0Eke4sSOol5xI8aixE4USSBmvq5BtG7eVDc9ppSoUuwSRutmmscI7TJi\nHV3k/U7f13J160qBToSIRe1XF9UzvT9QnNwB5YzebeMFQUVU9E5crL+tDaXLJg86GR+Px5jP59pU\netmeRxa4KKIimMpdkgbDeexPd+E0aUcSGspegNyJkTvL4Hh0YidXvlLBRhKxk0Uu2Nfp66Z7vXTR\nOrmxr25KRxqxMxE4HaZiZ9KeJLxf/Vo7mbQSt2nKKHdVYF0XZN1i/bSNcuskEmXDJJVO50o3XaGK\nbOt7qnJCl4a819TJUbuobZMKXtLonanckVj4gkDEihiJYMwvhonYuXYb7ukonCip9KxGbLQOAOaa\nAfZx49d82JFpWDmNmhVZ7JIKnH6/q2vtkhRamFBkRM4UTs2Wm6hGuWUec5UnVZIHXfRuMpnA930M\nh8NQKr0qz0umSuckTyondHlMj8izR13UtiqSNhNOEr1TyV1UhChOxFSzZqOOWbU/uSp3cUyn0TbN\nvnTROjliFinnlmUcrctb4mRUrUrywDQCZzz3tQQCFwdH78pNmrYoVb/4VvX4xehdt9vF/v4+Op0O\n5vP5SvSuSm1sdPOMt2E0YeWEbpPr6YBkPeqSVsMmid7FyZ3YrDa22MEOR+1UIhdsG5Mapf25div2\nGH2rERutA9QTKxb3j17fGBWtUzXzzQsS67wFKY8Uqkl7FKLsglek3FX1Il0m5LYonufBcZyVtijb\nWI1YVih6JzahpvMl970r6+8H/e6W9fiKpHJCJ1LkerqofaZJ4UbtjzCRpWBbjdxFFTsA0XLnWQ14\nDbNj0B2r+FixPeOgj9apUqpx5yNO7NJUjJogVyQTeRQU5L0OLkn6dV0FEXnAqdlyt2qwLAuNRgO9\nXi9YyzWfz+E4DmazGXzfx2g0qmRblDrIv/wc5LV3YrT1+PgYQHmbUNfhfKSl0kInknePOtonkJ8s\nmgpomsgd7duOOQZVwYNKGkxTw7RdlCiYRBZJ7HRyBMSfD5XYKcdq5dBAM+o4VZj2iNukwEWRV4+7\ndZEkeud5XvCnrEJUN2zbDqJ3juMEKb4i2qIUTR0EIu45xEVby7RWclsrXIEaCF3WHnXBfnIslshz\nn4BerlQXV084hii5c+1WELmKS41GRQ7lqJdp2lh+TFm8TF473es2O43u6cUvunBCR1KJUyGLURGV\nqHlJHFAdgYtClju6IE2nU7iuG1T3HR4eotFoBBV/ZReJukDpMTF6x21R1ksSKZWjrfJaSd/3g/PV\nbDbX/ntUB8FOS+WFziSKZrQfQxlLkkYtYmKFKABxEUGSO1ns5EIJk9So+NiR0TjTyJ7diJQZk9dO\nPvdy8UF8RC9e7OZ2K/N7SyavSlciT4ED6iFxOuTU7N6FC7AsC/P5HIPBIEgDOo4Dy7Lg+35wYdrW\ni0TRyBfgvNuiFE0dBCLLc1BF72azGabT6UaidxyhqwFJ16vF7q/A6F2e48hM9kli51t2rGQRKrlT\nRaiiooD6dXaKGXsRUhW1Rs4kapZE7FQVqVm/NOQtcABH4fLixksvBf8+c+ZMqAUHsJCL8XgM13VL\nnwasg1jIVKEtSpnXLpqS13uHone6SmeK3hUp5NscXa+N0MmkqYbV7qvCcidf+JNE0ICF2EVJky4K\nKD9mXINdk2gZPRcvpczoXs9AuGI+z5KcD47CVY9nnn46+Pfu3p4yDUjzMik1W4Y1Q1UniUykaYvC\nxFPUlwExegesR8g5QldztlHuTIpEotbG0c+8hlmKVyd26qheVNWrWuzUUb307WiyCpcqaldmiWOB\nS8b+jRuh/1++cmUlDeg4DovEBjFZqE8R1SQD6pNSh8joup6DLORFpNPrcD7SshVCJ1JnuZMv2mmr\nauOOL07saH+6xzSJEpLYmayzMxW7vAsQylqRGuyPJS43xOjd5StXgouO3G2fog5lTs2WjTwuwLqF\n+mIFrcmA+jTUQSD8HCr/kxKVTheLYZKeM10KvOrnyIStEzoi74Xum5I70yKJqMfVXfiT9uGTBcdk\n7ZkqSqiLdKXpCyhX4WZtMl1miWOBWw+y3MUNrhejREVeVDZxUS4rcvSOZEFsiyI2yc1CHYQO2Lzw\n6KJ3dM5Mo3d1OR9p2Cqhy1vidKSpmE0qdyoRSCqVplMvoo6NhCmrxM6FEWFZXi9fiBDqfh73ODIs\ncYwOUe6Azadmq3ghK/oCHDegPm0kqE6UTYLk6J28hjXqnHFRxJaQdyWs8eMmaMEBRMgKrKABb9R2\nUY8py4RJ2lI+NpXgJJVJ3X6SHhO9BmmkK+px8pQ4TqVuD1GpWXGNl7ggPI8oEWOOri1K0kgQUTYZ\nSkPZK3Xjzpm4zIGLIraUPNfTGT9mQrmL3FeKNXJZxpktii0MjitmX3ntR5autOeQHidPUeIoHCPL\nnTz6So4SrSs1WzY2KUR5tEWpi9BV5TnoonckeL7vYzKZoNPpbF3EdauFTqSscme8L+n4dRKQdJxZ\nVvLal4l0Je0Xl7coscQxOkxSs2KvLpK7JKlZXkOXHdU6LkqZpz0vVaBKQicjR+/29/dXxshRJLzu\nsNApqJPcmWyTtUgi6XHktR+T7U2fWxpY4Ji06FKz/X4fruuG2m/Qz0xSs1W9KJcRMRIkTkCQ26LQ\n6LgqU2WhU9Hv92FZVnDOXNet1fPTwUIXg2mLEJF1tUPJi6Qp3sjoXkaZTHpMJo8VV/yRaH8scUzO\nJE3N1m2uadnXbwHRExAA4OjoKDS/tGrnpW5CR8+Fond1em5RsNAlIO+1bUb7MqxwlbcpEtP0bpJ9\nZd3Pyn41xR9A8teIJY5ZF1lSs8z6EPvaTafTYA6wOCauSgUvdRG6ba5wBVjoCqcouTPZRleQIJJW\nAJdr2rLtK6/9iPtKsl1UAUgesMAxWYhLzYopQMuy4DgObNsudDJC3tRBJui8VLUtSh3OAaB/HnV4\nbiaw0K2Rda/Ny0MAk+zPuHVJTvsx2VccebcUAVjimGJQpWYpBeh5Hg4PD+F5Ho6OjmqZmi0jKoHI\nuy3KOqi70G0LLHQbIunavHULoEl6N8m+Nr2fomGJY9aJKjVr2zZ6vR4ajYZyRialCMt2wavzRVjV\nYsNxnKBBbqPRyH04fVLqVB3NETpm4xRVSJBFAsvcuiTTPnJ6jVjgmDJBgndyfBxKzQJYSc2KEaIq\npWbLSFIZtW0b3W63VG1R6DnUQXrq/OXABBa6ClJEcYYPK5coYNn2Q/sy+ZnJa8QwZScqNSsPrS/D\n+q4qX4SzHLuuqbHcFoVSs0W9RlV+/WV0LWTq8vziYKHbEkwqU9Os8ctrP6p95bWfNPejx2OJY6qM\nKjUrDq1Xre8qa2q2jOQpQ7q2KOPxOJC/Itqi1C3lWpZ1iZuAhW4LKarxcNL9JNlXXvsxhUWOqSO6\nqllgGSGaTqcrEaIiU7N1ihDlBbVFabfboYpmuS1KXuemLq+/Tujq8vziYKFjYsmzyW+Z9sMw24wq\nelfm1GwZWYeMWpaFZrOJZrNZSFuUOgl1nZ5LGljoGIZhmJXonZiapXFkRbTeqPJFeBPHnndblCq/\n/jJ1ei5pYKFjGIZhQshyRxEiYJmadRwHw+FwbalZZpU82qLUSYK4bQnDMAzDaDBJzYqL90nuTNN/\nVV6UXzYZUrVFEUfFqYpeyvYcsqCrct0WWOgYhmEYY3SpWVq8nyY1W9WLcJllSIzeqUbFUWGF5xU/\n/3tdcFEEwzAMw6QgKjUrpv8oNSuOI2PWi64tynQ6DYRn3U2N80Yl2FV9LmlgoWMYhmEyo0rNiuk/\nEoijo6NQarbMUa44qnrsYlsUimpZllXpaSJVTt3nBQsdwzAMkztxqVmqzASAk5OT0FSEqlCXRraN\nRgOdTqeQtijrQjfCrKzHWwQsdAzDMEyh6FKz3W4X+/v7aLVaytRskSOvmAVylFFui1Jky5o8qWq0\nNE9Y6BiGYZi1Iadme/2+MjV7fHwMAIWNvMqDOkhE1HMQmxoDCKJ3JHi2bYda1mzytfA8r1SCuQlY\n6BiGYZiNMR6N8Mxp6lXV0DhL09yiqbvQyeiaGsttUZrN5trPz7b3oANY6BiGSYAf8eFoJViUHLWf\npPti6oMuNSuu7ZKb5m4yNbttQieia4sizgJe5/mpw7nICgsdw9QQWZiyCFKcfKm2Uz2e6X7S7Cvt\n81MdE8tkOVBVzYrRoSqlZstMXiKka4sinp8i26JwhI6FjmE2CglFHhIRJUxJBCiJeBW5jyT7ihPA\nJPtLui8WwPUQN2uWqjJd1w2NIysy9VeHqFAR7T7ktihyU+Mi2qLU4VxkhYWOYdaMSiiSSETUftIc\ng+X7uQrYplG9lmmfn8nrlObcMdlIk5otYuF+1SWCZK7I5yAWVhTZFoUjdCx0DLMW8ko3FiFedZI5\nmU1GCgEWvHUQl5qdz+dwHAcnJycAODWrYp2vQ1FtUei+2wwLHcMI5JUCzUsk6ixb2wBH79aPHL0j\nOSgiNVuHCN0mjz/Ptiibfi5lgIWO2Wp0wrTuFChTf1ju1o9JapbaoqTpqVZ1iSjb8Wdpi8IpVxY6\nZgtJKl7rToEy9SfNe4olMBtpUrNRVZl1mB1aNqETMW2LQgJe5ueyLljomNKSZ0SDU6BMWcmrLQyT\njKjUrOd5cBwHk8kkGEemS81WWSKqJEG6tigk4J7nYT6fr0RXq/L88oCFjikVeaVAWbyYOsNyly+y\n3DUaDfR6vcjUbF7tNjZJlYRORNUW5ejoKFh7R3Lebrc3fahrhYWO2ShpxEt3MWOJY7YRlrt8MUnN\nktwBwHA4LLRhbpFUVehELMsK5HpnZyeUPnccB71eb8NHuD5Y6Ji1s+5WEgyzLZi0TeHWKsnQpWY7\nnQ6Ojo5g2/ZKw1wad1V26iB0wPJ50B+K3lXhHOQJCx2zFli8GGb95D1lY9sR5e7SLbfAtm1lapYa\n5iatml03dRO6bYeFjikEFjiGqR4cvTPn+rVrAICT01mlutQstdwguStTarYuIlSX55EVFjomN1ji\nGKZecPTOHF1qVmy5UeQs0zT4vl+LtCT3oFtg+YbNdL7x9a8XfSzMmshroDgLHMNsJyx35ly+ciX0\nfzE1O5vNglmmVDm7Tgkhuex0Omt7zCKYTqeYzWY4c+ZM6PZGoxFModgGjIVOhOWuWsSJV5IPZ5Y4\nhmFEWO6SIQqemJp1HCc0DWEdqdnj42O02+3KC91kMoHruhgMBqHbm81mLdrLmJJK6ERY7spJWvEy\nqYpjGIbRwYJnjhy9o9Ss4ziYz+eFp2aPj4/R6XQq369tPB7D9330+/3Q7Sx0GWC52ywsXgzDlAmW\nO3NkuaNpCI7jFJaaPTo6Qq/XQ6vVyryvTTIajWBZ1krPOdVkjzqTq9CJsNwVDwscUyS+r5kpavFF\nmkkOy10ydKnZ2WwGz/NySc0eHh5iMBhUfp3ZcDgMxoKJsNAVAMtdsbDYbTeieGWVLZ3E6dA9nrwf\nlkBGhgXPnLjUrDhrNkmK8eDgADs7O5VPS+rWArLQFQzLXbGw3NUfU+kylaikEpcVljtGhuXOHNPU\nbKvVQrPZjIze7e/v49y5c5WXHl3quN1ub1XrkrULnQjLXbGw3G2WKFFKKjVZpUt8vHULXBQmx8UC\nuF2w3CVDTs26rhvIXVRq1vd97O/vY3d3t/LSo0sds9BtCJa7/GCR2xxpZMk0bclEy12eqWdm/bDI\nZUeXmqU/YmrWtm3s7+9jb29vQ0ebH7rUcdXbsSSlNEInwnKXDBa4zcLitRksyzd67Vnuyg/LXP7o\nUrOUnrUsC57nYWdnJzY1W3ZUqWPLsirfjiUppRQ6EZY7NSxxm6WsEudjdS2MBa9W+8qCaeqZJXBz\nsNwVg5yadRwnqA6l1Cz9qdKaOl3qmIWu5Gy73LHEbY68BY4EJw+pUcmSjrjH89CABbOPhLh95Xlc\neb5eSeFK3s3Cgpc/l69cwXw+x3A4xLlz5+B5XrDujlKzYs+7MuN5Hg4ODlZSx1Qcsk1USuiIbRE7\nFrjNUpTE6UgiK0lkyeTxPKg/tJPKXZ7HlefrtW5Y7oqB5S5/TFKztO6ujKlZ13VxfHyM8+fPh25n\noasgdZM7lrjNsm6J06GSFVm6TGVLh4+EPeciHo/2lfWY0qJ6veTXflMCyHJXDCx3xaCqmiW5K2Nq\nVow0irDQVZwqyh0L3OYpi8Sp92XYc85QpJJKXNTjxe1rU3JnAstd/WDByx85elfG1OxsNsN4PMbZ\ns2dDtzcajcpPwEhKrYROpMxyxxK3efKUuDwFbrG/9MemkihvJVKV/ldePjbzlOzqdqrnWaYIX+GP\nyXKXKyx0xVLW1KzjOJhOp9jZ2QndzkJXU8ogdyxxm6XMUTggLF15SE2ekb28o4SmmKR4i3lclruq\nwBK3OcqSmp1Op5jNZjhz5kzo9mazWfqCjrzZCqET2bTcsditj7wlLkkFqNn+4hb9J3ss3f7SRtFU\n+0uzryghTLq/PPaVBE7NVgeWu82hSs2Ks2YbjUaQmrVtO9fo3Xg8hu/76Pf7odtZ6LYMlrv6UYTE\n6UgjEHESl/Sxku4v7pg92JnSqPK+bEMhyjsaZ5riTbZPlruqwHK3OaJSs7PZDAACucsjNTsajWBZ\nFnq9Xuj2shRtrJOtFjoRlrtqUkSD3yiJU2EiNnlBj5V1n+IxR+3LRHZM95VU7vIouvBhJRJvlrv6\nwXK3WeJSs/I4sqRQc+Rutxu6nYWOAbA+uWOJS0cZJE4HCYGbc2QPyLe4AQA8/7RZr4EkxEprgn0B\nermTn2PaCF/WaFySbdcldyxzyWCRKx+mqdlWq4VGo2EUvTs5OUGr1VqZ28pCx6xQpNyx0JmzzlRq\n+n3mm/403WcSSSHxUu7HUBiCKGEO+yJhM3mecXKXtBdeVeSORS45LHPlR5Wanc/nQVsUwCw1e3x8\njE6nszLmq91ul64JctGw0CWA5W59lDkKF95nHpMRwr+Crr96nFmjaHN/Ub5vHPGKeDw6vqz7Sjs6\nS37cPIsu8tyW5a48sOCVH11qdjabwXVdbWr26OgIvV5vpYkwCx1jxPve9z78rz/+44Xtf1vlbpsk\nToYkKU4WkogdSZyKNDKmEs00+zI5zybP0/ct2Ja5NLHcMQDLXRVIkpo9Pj7G2bNnVypa5RTsNrBd\nXfdyYnd3F3/113+Nt7zlLfA8Dy+9+OKmD6myVCGVuthvcRInEpc2FF8v1QVdljiT6tgoIZt5i2+9\nUeJkui/x+camT0+fp/wc5feLmPaNkzvTatkkVbXm+8x/DFnce4FhqsozTz8d/PvylSuwbRudTged\nTieUmj05OYHv+xiPx0H0zrKsrYvMERyhS8EHPvABXL9+HX/1V3+Fb//2b8cv//Ivw7ZtzOdzjIbD\nVPvclqhcVaJwi/2uR+KiMKoytfzIaJzpfkTJ0u3PNCIm7iuPytekqI5Tl5pNcgzFRPnyfQ1Y7lbh\nqFx9EKN3nufh4OAAvV4vlJrtdDorkyO2AY7QGTCbzfDlL38Zn/vc5/AHf/AHePHFF/GGN7wB733v\ne/HmN78ZvV4PruvCdV3cfPFicL8Xnn/e+DHoA6eOYlcViStC4IDkEicSFbELpOv0R1EXcpOCAQ82\nZn4TjQjBMI2IOf5yPUvTciMfM9if4nF15yROwug4bcuLbX9iGmEE0kX54rcVp4TkG7kDWPCA8Ocq\ny119oEhcr9dDr9cLUrOet5m2QpumEjW9X/ziF/HqV78ad9xxBx566CHlNj/xEz+BO+64A695zWvw\n1a9+NdF943j3u9+N++67D+fOncPv/d7v4Xd+53dw11134fu///sxGAwALN5YcrDz5osXgz+mWL4f\n/Kkyvm8Ff3LZH+zQHwt+8CcLHuzgT57M/Wbwh440C+I+aL8r2xi83qpjmfnN4A8AuLDhGrwenm+v\nVLrO/QbmksCqblPuTzgPcefE5Jz5sOD6DeVxxu3X5P3gC+/CvLYV3+N5kffvYtXxLSv4w1SHy1eu\nKCtjxfQqpWblqRHbQukjdK7r4r3vfS8ee+wxXL58Ga973etwzz334M477wy2+cIXvoCvfe1rePLJ\nJ/H444/jx37sx/CVr3zF6L4mfOQjHwkN+X388cdxcHAQ2kYldCJpInei1JX9w6eIi4XpRc20ES1R\nVCQuLu2ZtK2GiBjxAhAZRdOtP5OPJU6ySOqiHgs4FTuD154eLypit9hmeVxR2wLq6JrufSBLXVz6\nuIjIXZJt81p3xxE6PRy5KzeywMl4nrd1veaiKL3QPfHEE7j99ttx2223AQDe+c534pFHHglJ2Wc/\n+1nce++9AIDXv/71ODg4wLVr1/CP//iPsfc1QZQ5YFEUIQsdIX9jUFF3uUtL1qiEbn5oUQIHxEuc\nClOxkyVOxES2dGLneKv7jZKbqMeaKZ5/I0bCRJEkYdPJpWpb/XGaF10AyQoqNi13i22Tp2ZZ5uJh\nkSsXcRInorvebmtRROmF7plnnsHLX/7y4P9XrlzB448/HrvNM888g2effTb2vmnY3d3F/v5+6DZ6\nA5kInUhd5E68cCSJ1uWZWgrv1wr9nSdpJE6FTuymXntlW92FOYnYqeSLENec6RAfK2pftGYwTuyA\n5XM12VYX4VOd4yQCZsFPVDGaVu7osXTHkARTueP1dNGwzJWDJBInkvR6W3dKL3SmJ2udxbrnz5/H\n4eHhyu1Z31jbKHcWvFykTheF00XtkpKXxKnwYWHqtaPTb74V3exXI3YTN9yLqWHHpDBjxG7mtjAz\n3JdYDCILm1wokkQC58G2ZlEqnYClbQ0j3j9J8QMQfg8WVeEb+fjc6iSE/JnJgrc+0kqcCEfowpRe\n6C5fvoyrV68G/7969SquSG8EeZunn34aV65cwWw2i71vGlqtFubz+crtcevokkByZyJ2ZRE5FZbl\nG0kdkUTu0o7aMhG7IgWOkCNxpj3oTMRu5qrTta53KkMGYidKnWp/pvsCzCt9oySQWBaHhPcZl5IF\nwu+ZBuK3lwUojxSq7n247lYncV8SthFeU1cseUicCEfowpR+NeFdd92FJ598Ek899RQcx8EnPvEJ\n3HPPPaFt7rnnHnzsYx8DAHzlK1/B+fPncenSJaP7pkW1EDNPoSN0lbJlr9RKW1lnwdNerMRKwSzR\nNl11rOs3gj9Zq2d1TL128EdH3POLel0n8zYm8zbcmNfd9RqBkOmg6lCdHCbZFwDMvEbwxwQ6F0Tc\n60LVtCYVtcBizR39McH3reA1MamaFd+rJlXZyapm01fDWpYf/GH0lPnztUpQdWreMgdwhE6m9BG6\nZrOJD3/4w3jb294G13Xxrne9C3feeSd+8zd/EwDwoz/6o/i+7/s+fOELX8Dtt9+OwWCAj370o5H3\nLYoihE5ElLrnX3ihsMdJQ95VriR1Uf3mkla3yogXZdU+su6fiJK3KEgEtD8XIiyT+epjkNQ1oiJ6\nEVE2eZ+tuBSrZl8qgaPb4vYJAHNv+TFlEg0EkhVTAFiROpPonUlRRdpoXJHFEiaR3m2Ho3PZKELe\nVHietzLya5vhSREpefOb34xPf/rToTfTZDIJZsytk03LXZ4yl7VhcJR8maT9IiNjCcQurcTpUF3U\nx/Pl+ri4Ks0oqQttZ7tKORQxkTAAiZKCun1GvbdM5U7ERO6A8OudZq2byVpA3eOp/p+GJGlZlrtV\nWOqSsS6JEzk5OUGr1VqZ29pqtbaynUnpI3RlhQoj9vb2gtuKjtDpuHjzzcG/NyF3aStcAVWvrdWF\n5omORYqIpB21lTRiJ7YCKaKyVlxfJ4ocEVfMYBKtG52KXJywmUTXHCGq1rRX15vq9kn7NXkfJVnD\nR8RF7lQiJa/V1Ame+NonibDR9rRdVplLs76OiyVW4fV08WxC4kQ45RqGhS4l1LqkDEInUgW5i1v3\nk6Uy1XQ9VBwmYqeLwuWVqhUZzpYSFyVlcjGDjErsRlJEzjQdqtpOFDmCUqYmYgcA09M1e23D7cX1\ne2nlrmWZPRawWjUbFx2NS7fK/99ksQTLnBqWuzCbFjmCiyLCsNClRNVc2LKsUs2QK4vceRlmmcbJ\nnXhxVcpXhuih+Pg+rJVGv7Rv3X6zRhuBsMgRcdE2o55yvhWIk46Z1zBKr868hlnlcIzYyYUGohym\nkeLTiCQAACAASURBVDsgXvCozUvSKRLAMlKXpEExkDwax82HmTJQFokT4QhdGBa6lOiEbtMROh3r\nlLuVZqYp25LIWPDhwdbKQ1xkLE7AZFYETiNoUftNE61TSZwK17dSR+tOnOVjtBr6C79JtG48X75O\n3Wa8eKnELq5qNI3cAdHRu6hmzFGCF7WmLk4Ms0bj4gplwtty8+G82NaoXBklTsTzvBV521aZA1jo\nUqOaFlEVipa7qN5zSeVO1WsuVtxSiJ3cd043mzQq6hb9vKOjdaYSJ2MidcBSLESRI2auHSl1gD5a\nJ8ocAEzmi9fRVOxm7uL4OgbbEyR3ScQOWMpdIFkJPvdFOfZgGxdKmERLRXSCl3VdnQ/bOGLH6+kW\nsMSVH9/3t7L4QQcLXUouXLiA5557LnRbmSN0Ir7vw3VdzOdz9Hs92LaNZrOJA8X0i7SYpDrpAuNH\npE1N1rKl+blYLKGKDtmn91WJXeQxGUbr0gqcCpOCh/1xLzoSZyh1wCJaJ4ucjInYkcwBwPR0e1Ox\ns+CvtEOJSw/LUmXamFglY2kKJYBk6VP5/ZtG6rKuqWO52w529/bgOA4AYDgcot1uo9lsljrapbvW\nlvmYi4aFLiW7u7v4u7/7u9BtZRY6z/MCiXNdF41GA81mE+12O/iGU1TkLkruTFOwWaJycnNamSDy\nUqDYjeZd5XHniSpadzhZimOctJFgxYnd/mTxXLrN+PV1OrETZU6ExA5Qy12U1MiVsiImETJZ8Nr2\nTLPlKqLgNQ0LLJJG45KkZ/OYJAFst8TVvRDi0i23oNlc/r71ej24rovZbIbRaATP89BqtYI/ZYuE\n0fq5bRY4GRa6lJR9DZ3v+yGJ8zwPzWYTrVYL3W439peg6LSsTuSyRN3o53RxVQlalITlKXZiaxHl\n/iz62cqPMkFSJ4qciFEkTrPNiSOnVxtGUrfYtoluc64VORVy1C5JhIrkjgTXNOUJLCN16vOm34+q\nSMLkfoD6fZ2k+fDi8ZP35VMeyxZLnI66yB2lUw8ODpRrz5rNJprNJnq9HjzPg+M4cBwHw+EwCAC0\nWq1SNPPlCtdVWOhSohI6YlNvNEqlksQBi2kZnU4Htm2nPqYscpdlLZ1JVC6qTUmUoOUpdhN32fYj\n6mKuE7s8pe7GaBkJbGvEzSQSJ28jyxwxmS9efxOxO5osXqdeK9nat+m8CXrrdhrmUTMxWjlXtFOR\nq22NZsEqih5M1tPp3hdxo8BEVNuGRTB5hWuwPUucMb5lVUrqVGviTK5Rtm2j2+2i2+3C933MZjM4\njoPxeAzbttFqtdBut9FoNDZ2veMK1zAsdCnRRejWje/7QRp1Pp8H6+G63W4midORVO6SrKUD1HIn\nXrTi1i6piijyFDux95xqXmq0vHmFSJ0ocSKOa2ulDjCL1ulETiYuWufMl897PBPSPDFyJ7995VYr\nKsEznYoxl5ofz/2G8SSJxeMstk3TN47eJ8lakiy3jZPI1YbdMdvzOLBYqi5xIkkzSZZlod1uo91u\nB9ec2WyGk5MT+L4fRO5ardbaroOqCtdth4UuJTQpQobSrkW+0TzPCyROtx5uHZDc+b6PF158MXb7\npIUSaearBmmvjGInTn4g5KkTJA46sUsqdYtjW/mRlheHPeH+6jtmkbr90fI16HfiIz66aJ0oczIk\ndyqxM/kVkgWv33Ti7yQgR+nkdXTAauQubqyXTvCSNCBWyV2aEWTLfdun+zUTu+A4tlzw6iRxBMlc\n2muUZVmBvPX7fbiuC8dxMJlMVlKzRV6PdBWu2yx5LHQpaTabcF3F6KAC1tHRejiSuKTr4dZBv9fD\nYDCAZVm5RO4sIampmu8at5bOVOySjAZrWK5ye53Y6QQySwpWlDgRz7dylTpR5gBgNF0caxKxsw0i\nVYQsdknf0lQEIVe+yj8nTKdWAEvJa53eh95TpoIVFMhkiMZtYhwYsN1VrlWQuSwtRvK6bjQaDfR6\nvWDdHaVmi153x2voVmGhy5m8hE5sLULimMd6uCKQjyXvtKy42DtK7qLEbuarU4e6iBlFZeSIDUVn\ndGKXV7ROlLqXhsuUatrpE6ZSJ4uczGhqG0kdCeCZTrKF+uPZcr2c6Vo702kWRLsxD85fXLRtsX/N\nZAvVlwVBnKIicnFpWlkW06R1udI1G2UthMjaJ65IEbJtG51OB51OJ1h3N5vNCll3x2voVmGhKxG0\nNoEkjtbDrTuVmgZdqrkoudOJHV34ZOESL5Ar6/AiImZJxS5NtE68TV4P5yquyTqpi4rSAfFSd/Wl\nRWXsmV60CMRJHckcAJxMF6+PqdiJbx9xrR0hS56JzBHtxqqYRUVou42p8b6JUOQ4wbo0HxYaCapU\n9S1PWOKKYNNyl2ez33VFtsR1d/1+P/d1dxyhW4WFLgONRgPz+TzUyydphE63Ho4icXUirdzpxI7W\nBakiJVGRNF06VoyoyOKVRux00br9cX/ldkDdm61hr0fqrh0sI3MnY9tI6oDVFKwocyImYmfy2UyS\nR33tHLeBdiNahFQiF0XrtP+cqxlH1lBE3qJkLG5dWhKRUyFXuqaVOpY4M9Yld0VNbNiECBWx7o6n\nRKzCQpeB3d1dHB4e4sKFC8FtcUInr4fzfR+NRqNU6+HSkFRkk8ideKHxIgQNWJU0MaWmi9olKaBQ\niR0tzNet33Lc8K9Zq+Ep5U13e5FSJ4qciInUAeFonU7mQvvViF2St73cpNhxI6JszRnmntD019Y/\np5ZhI2FR9FqnTYQTzVj1LaNUbxz6BsTJKlzF42Kpi6eKEidShsiWbt3daDQKroeUmtVBjY9lNv3c\nNgkLXQaodUmc0FVpPdwmILkzidrZwoUwSu6SRO1U95Ejcao+ZrrRU/Lt7cZcKXXAalRunVJ34zh6\nkXISqUuKKHZZZC5621VBE+WOoNYnSeauthTTIOIaYQPqNXsm94u7PYok/em2uQgiiqpLnEgZhE5E\nt+7u6OgoSNu2Wq2VUWRlex5lgIUuA7u7u9jf3w/dZlkWPM+r9Hq4NORRDJI0JRsld1FROytY52Ze\ndUVVkaLY6QROdTul/UyidUVL3dXnad8+Br3oD0QTqds/Xh7r7k6ydN9otnoOBm119MpU5lQip0PV\nx061lhJYjgJLIlU+wtE400hekp5zpiRNxW673NVJ4kTKLELyujtKzYqjyEjwuChiFRa6DMjNhcVU\n6nw+D9bDVTmVuinSyp3nN7QLxuWpElHpWN2auaRiZxqtM5W6pMhSt5S5BcNxNqkTZY7+byp1uu81\nQ0cteRNhzqtO7kxlLsnECXmma9w8YUKXVjWtWM1D5PIqktgW6ipxImUWOhFxFBmAYM7sZDLByckJ\nAGA2m8G27SBIUoXnVSSWX5bhoxXkwx/+MI6Pj3Ht2jVcunQJP/IjPwLbtuH7Pnq93la9uSaTSbD2\noUhEudM1JyZUlbCEbmSYLmqnajirSsMC6rV08m2y1AHqogjVbaooHaAXDQB45oXo1ypO6gB19ass\ndCJRYpckSK2L2IW3MWsobNp42La8FZEzQZa4pClSkrgsfee40jUZ2yBxIuPxGL7vo99XF2dVAc/z\ncHBwgFarFQRPKHpX5eeVFY7QJWQ0GuGxxx7DI488gk996lO4+eab8QM/8AN44xvfiH6/D8/zMJ1O\nt0rmgGIaKqu4ePPN8DwPruvixv7qpA6RqP51VFmoi9qZROxU0TpAHbGTo3WqFKxppC5p6hUALt/s\nR0pdmkhdlMyJP5fFbhMyl2SCRKex2DZKkNNG41T3VUXikjQhXmzDEpeEIiXu3PnzgVyUkapE6KKg\n4z9z5gwAYD6fB1Wz2yx0lY3Q3bhxAz/4gz+Ib37zm7jtttvwyU9+EufPn1/Z7otf/CJ+8id/Eq7r\n4t3vfjfuv/9+AMDP/MzP4HOf+xza7TZe9apX4aMf/SjOnTsX+ZgPPvggPvjBD+Kuu+7CPffcg/Pn\nz+Opp57C+973vmAbz/MwHo8xGAzyfcIlhyS2qA8xSmfP5/NgUkaz2QwaVF5/Pn70WLAvXXROuF1c\nR6WK2qlGgzmKiJ0cies0ZqmidVkidV+7uvx3r5tPpC5O5mRI6vKUuaJEzpSmojAiCWnbleTdcw7Y\nDpErun/c5StX4HkeHMcJFvZTq44yrZ0eDodoNBrodtUzoKuA53k4PDzE7u5u6HZqXrytVFbo7rvv\nPtx0002477778NBDD2F/fx8PPvhgaBvXdfFt3/ZteOyxx3D58mW87nWvw8c//nHceeedePTRR/GW\nt7wFtm3j/e9/PwCs3F/mG9/4Bs6fP4+9vT0AwBNPPIHf/d3fxS/90i8F23ieh9FoFHxz2BYcx4Hv\n++h0OrnsT2zvMp8vLpy0JjGuy7ip3LmaAPXcV9+uS8fKcmcidqqmufLaMVlokkqdKHJEHkI3y+Ax\nF86ZSYhK5sZCAcW5Xrx87bTMGgO3I0RO1XMui8hl7TkHhCPPWWCJy05UStX3/ZDcmbbjKJqTkxO0\nWq3cPqs3geu6OD4+XgnibLvQVTbl+tnPfhZf+tKXAAD33nsv3vSmN60I2RNPPIHbb78dt912GwDg\nne98Jx555BHceeeduPvuu4PtXv/61+NTn/pU7GO+8pWvDP1fV+UK1COsvW6ovQsVlQAIikqStHe5\ndPGm4N9RctfA8sIsyp14wRblTldEQWutSOzawqgokjs5xUoTD0SxG7TdkNQNnQZGk7DEHY9Wn8fL\nLiyO6+tPx78+44kfKXVxqddnri+O++KF5B8drSZwNIyPUpw/44XkTSZO5kxELkriRMSec21rcZ6T\nTIAAwinVJP3qwvtgiTOlaIk7v7trFOGyLEvbjiPvMVhJqGgMJwRXuKqprNBdv34dly5dAgBcunQJ\n169fX9nmmWeewctf/vLg/1euXMHjjz++st1v/dZv4Yd+6IcSH8Pe3l6oyhXY3jcUtWtJitijbz6f\nB+1der1eLimKouUuSuwWt52KXITYRUldv+uFpG6nvyp1z77UwHhs/tqnlTqSOQB4/qV5IqlrGW56\n/oz+eUSJnOvZ2GlPFv+OKJbpNvXr41SiRRKnQleUY1l+ZIWqaZWrPAFieXuy37NtkLiiESNxJycn\niT/no8ZgAQjkTu61VhRVv05xwERNqYXu7rvvxrVr11Zuf+CBB0L/tywrta0/8MADaLfb+OEf/uHE\nx3f+/HkcHq4uzNfNNa0zSYoi5B59lEotep1JGrmbYylnKokTo3aOv9i2QUURpxMkFhWTq2Kni9al\nkbpez16ROtsCPM0pSSp1oswRSaUuDhOZcxWNgUnkougarKUj0RIlLmlxQpoJEEl7ziWdBJE0olh1\n8hrNVVSFqjgGiyYl6HqtFXENqcO1iSN0akotdI8++qj2Z5cuXcK1a9dwyy234LnnnsPFixdXtrl8\n+TKuXl0uJLp69SquCL+kv/3bv40vfOEL+JM/+ZNUx9doNJRRqXVVfFYJ3czaTfXoM5W7JpYXd5I7\nber1VARI7FpCrzOSu+bpmqyJ21wZLyaKHa0hI7Ezkbq8IalTyRxhInUm0TmVzI2mi/fFxbOzWJFT\nNQPut+JFTyQqGgfoq16zFkdk7TdHgpdkCgSwHYKXVO5MJC5PIbIsKzQGS+y1lnbGaRx1EDrP80pT\nZFImSi10Udxzzz14+OGHcf/99+Phhx/G29/+9pVt7rrrLjz55JN46qmn8LKXvQyf+MQn8PGPfxzA\novr1V37lV/ClL30pU7VP1X8x8kKWWCpqoHRqmWfWJpU7VdQOWMqdKAY6ueuepl5FsZvMKcLnw/UW\nr48YrYuTuryjdMBC6uKIkrqkMkcSByxETmbuWjjXXayR0010SCJycRKnI6vEAZtvHLxtkyB0cpc0\nElekEDUajWB9nmrGKcldlqKKOggdR+jUVLbK9caNG3jHO96Bf/qnfwq1LXn22Wfxnve8B5///OcB\nAH/4h38YtC1517vehZ/92Z8FANxxxx1wHCeoWP3u7/5u/Pqv/3ri43jjG9+Iz33uc6HbxuNxMHtu\nW3BdF5PJBN1uN1SZSu1Fqjiz1qRaVpQ7EWWrEz+8LUXtiIlQCUtydzJtotcKp2DjCiVU6+l0UgdE\nV74eHCVLIcpiFyd07Zb6wEjm5u7y2EjkVPSaZhWtANCxk7UnIeogcSv72gKRU3Hl8uXU9z06OkKv\n11trNSUVVVDVrG3bIblL8tm6v7+Pc+fOVTrCNRqNYFkWer1e6PY8I5lVpLJCVxb+5b/8l/jUpz4V\nkrd1TU0oA1TUMJvNQjNrG41GJSVOxzrlTid2wFLMRKkrUuiA9FKXRub2BmFp2rTEAZtPqQIscXmQ\nReJEDg8PMRgMNvaFndYgk9wB0A6wV913f38fu7u7lf5s1vXS23ah254QUkFQYcSFCxeC2+q+hk4u\narBtG41GA67r1rZLt0laVrXeDjBLy4op2VZjFghetzEP9bU7mTZxOLSx01+mX4tMvf7lX7yEV7xy\ntWF3FM+/NEenbeOm3fAH64v7y2N62cXVxyOZc30Lez112nRdEieeszStRvKQOIAnQGQlL4kT2XTK\nUiyqoC/UYlEFyV1UUUWVZQ7glKsOFrqM7O7u4uDgoPZCJ66HUxU1UEpgG7h48wUMh0MMBgM8/8JL\nym2yyB0QXnMHAO3OQnbOd4CLZ5p4/qQH11uMAQPMpC4KldT95V8snts3v3GQWOqAsMBFsTeYKyNx\nluVHCpyqbUheErfyWAatRljiykEREldWVAPsaQTWcDgMxI4iV5uW0bzwPK8WzyNvWOgyomouXBdU\n47biihrq8oERhfj8kkbudD3uSO46VlhI5n4TjUZYahq2i1ecnwKnjjWed05bnnQiK1+jonQyJHNE\nEqnrtKNTHi+7aOGVN50of9ZvLiJzUXNUCRKWtIUNQLo2I8Dy+PKY/ACwxGVlnRJX5s84sWKW2qE4\njhPI3SYnVOSJ7/vK1GpZz8u6YKHLyN7ennJaRJomu5tGNW6LyubjFt5u+y8SYCZ3Yo87YCl4sliQ\n4Mnrt+Z+Ey3ptlZrjl6zib3eMLhNHDXmeE382d8v1pqYpF5lmSOSRur++e3z2B5xughcVIpTFjgT\n+SPE1zPJ/URY4srBpiJxZRY6Edu20e120e12gwzKZDKB7/s4OjoqxRiytKjOQRXOSdGw0GWEUq4i\nVUq55jVuC9iuhspxzzXrhApVatayfLQkmdFF9sT79zDF937HMLS9zMxb3v66V4ULNv7PTy0e89/8\njz0A00Tr2ADAPd13t5HsfkRcUYJO/kjYdPeX7xcleCxx5WDT6dSqfK7L0KQKy7IwGo3Q6/XgOM7G\nx5ClZVuuM0lhocvI3t4ennnmmdBtZRe6osdtMWEu3nwheK2Pjofa7US587AULFlIXKgnVQBiZG9V\nQOZ+Q5tibDX00vQT76DHHWu3kQk9vh2fEpXXw2WtLE2TSpUFj9fElYPd8+eDdWBloaoyQalKej37\n/X6w7m5TY8iS4vs+R+g0sNBlZHd3F3/7t3+76cOIZR3jtsousnkS91x1r/fFmy8EHzxRkTtxGLso\nd0A4WuTKP1MIHt0m/0zXmFe+//JxV8WExMs0felB/ZgtjfTp5qWqSLseToQlrhxQJE6enFD0WKw4\nqh4Zko9fLKoQ5W5dY8iyULbjKQMsdBkpc8pVVdRQ9LitMjzvTSGPN4t6vT3Pw4W98/A8D/sHR5H7\nNZE7ii7JwkRTKJb3t7U/A1YlT5Qk2l4lWaq0p0rybHhK8dIJoU5ofN/KReDomPKAJS4bF/b2gkkJ\nNNpJnpwgVnAWMRYrjroJnYyqqGIymeDk5CQkd5vM5HCFqx4WuoyUSeh047bWtTZiG3/JklQC07kh\nKPVx6y0Xg22ffe669rEsyw+nZRXr4UQ5UUXDYn9uebHbqIQjSvLknm4qTIQwtI7Nit42irwEbnEY\nLHFZuOXSpeC9LzYpp9QgNSinP7TIXxyLJbbnyDPjUEeSXJd0r3eeY8jSwBWueljoMqISOmId3+Z0\nlamdTmftkxrKEpksEnq9fd/HZLKo4IySZlniaBi3uC19WM5mMwz63UAKX3xpP/JCb6+kUMMfrLK4\nrETv4IVEShdRi9rH8nkt99OAayxuUSJmwTeWr7j9ssSVh0sXLwbvd6q2pCkH1E9NXOerk7tOp4NO\npxMaizUejwuVjapH6IB04hP1emcZQ5aGOpyDomChywhNihCxLKvQik/xw8513WAdRJrKVCYelTQD\nUHZjJ9kT29aIFyNR4mh0D6VnaZEybfOyWy8F+3ju2rXY4xQFTxW90xVdECaypRI8VQWoqbjJ2yWd\nyKDDgp/bvhb7Y4nLwq233BL6P8kBfZmZTqcYjUbB74E4C1v8/QMWn6/y71S73Ua73dbKRl7tOaou\nE3kcv/x60xgyKqowHUOWFp4SoYeFLiM08qpoVIvs6ZtoWVIMdYrQ6SKfJM2TySS4mJDEkVwD8RJH\n6dlOp2P0wSdeEJPKnSodaksSlkTwxNtN23lECV5U9Cxpr7j8hJBnp+aBLHIyYuSHft9msxnG43Eg\ndzQbutForCwrIblrNptKuSPZoPYc64wklRFdujItqjFks9ks0RiypFRdqouEhS4HdN8WssqNvMhe\nHrfF5Isu8qlr5+K6bugc0/mhCC1tQ+kl3/cTSZyOpHInCoWualRXeCEKUlx61pQk0bO4SF8Zo3AA\nS1waxGgaRdpI7hqNRiAGstx5nofpdKqUO7E9B8miGElKur646jJR5PGLFbO9Xk9ZoSyOIUsLR+j0\nsNDlQJ5Cl2bcVlmoYoRO15NPFfmU06nz+Xxlkgb9XJS4VquFXq9XSFSgaLnzdWvmEqyFM9mfKQsZ\nXIpX9v2xxOVBWonToYq0kRzo5I5+90S5o985sfcayQalCX3fDx4r7osWC505coWyWMRCn5tpMkxU\nAc2swkKXA81mE7PZLNT40lRusozbKhtVGXmWpCefKp1KFxSKIgyHw+CiQc+/SInTkUXuAF2lavh8\nmgieD2slpavaXxIZ04lXmv2xxOVD3hKnQ07rkdxNp9PgCxjJHQ2gp89Vx3GUchfVe62INGFZ2JSQ\nmhRVmK5z5CpXPSx0OUCFETfdtBz3FCV0qtQefZPhooZi0Emcrr0IiRywTCXQBYP2R2snxbYL9GFD\nfzZ1LpPKHWAWvdMJlHi76TOOkrE00hUlnyxx+bAuidOhW7NFX6rElF6z2QzJ3Wy2aF4ty53Yey2u\nkTFH6LITtc5R/Jnuy3AZnkNZYaHLAWpdIgqdTJLUXlUpW8o1aaNflcSRmAEIreuhBdmtVguDwSD4\nZqmKIOSxbiQLRcidZfmwEF14kYQ8hYuIKwxJAktc+RDXbHW73RW5EyN3cjsUWg4hthAyaWQMoNKf\n12WTIXmdo0kqvGzPoUyw0OWArrkwfSssctwWEyZpo1/6Q4UMFIkTPzxEiSNBo2iqjC49NJlMQi0Z\nNh25+4WHgR97W3K5M9kmqzylJeo40xwfS1x1kOWOPnvH43GwjjWp3Kka647H46BKvYqNjMssQ+I5\njBpDppsUUdbntU5Y6HJgd3cX+/v7ABAsyKUPCQDaqFDd2ESELul0DN20BlniHMcJZIzWzOkkTocs\nd2LV3qbl7n+/F/iFh5cXbVO5MyFKnqJGeWV9rLT3ER+bJa76iM27xV53otyROOjkTtfImD47Go1G\nqAJ3U1MTklJmoZPRjSFzXRfj8TiQPF6mtMTyy5QjqyC+7+Pnf/7n8fTTT+PP/uzP8KY3vQm/+Iu/\nCMuy4Lou+v3+pg9xbbiui+l0Wvhz1hWSiO0KREymNciROLEHVt7fwFWPZVJhlze/8LD69jzlLg1x\ncrfN0pU3dZE4U+iLn9gLUm6CS3InrokluSOB63a7wba0wH82m+XeyDhPfN/H/v4+dnd3Ky1AN27c\nQL/fDz4/SdzPnj276UPbOByhS8F8PseXv/xlfPrTn8ZnPvMZTKdTfM/3fA9+7dd+Da9//evRbDaD\nlN82UWSELq7Rb5ZpDbRP1bSGIhAX/tJzotSC2CW/6A/dmeOi1V696PzGHxUTuTNFFUFjicuPbZM4\nEVXkjqZU6EaQiWtxqbCCWmdUqZExRec2fRx50Ol00O12A6HmuNSC6iT/Ndy4cQN33303vvVbvxVv\nfetbtXNVv/jFL+LVr3417rjjDjz00EMrP//VX/1V2LaNGzduxD7m/fffj5/+6Z/GzTffjM9//vP4\n2Mc+hjvvvBNveMMbgg+CshUIrIO8nzN9QE4mE4xGoyCd3ev1MBgM0Ol0gg9KisI5jgPXdYMP3Ha7\njU6nE3xj9n0f0+kUJycnOD4+huu6aLfbOHv2LAaDAdrt9lo/8OgYB4MBdnZ20Gg0MJ1OcXx8jNFo\nVOiH1X94T3wE4Tf+6Ba8/z9aeP9/3NxFgGUuO7feckvwh1lAadQzZ85gZ2cHzWYzkLHhcAjHcQLp\nm0wmcBwn+FI4nU6D2+iLo1gkdf78efT7ffi+j5OTExweHmI0GgXLQjZBldKtOuTXjoS61+tt6IjK\nReUjdA8++CDuvvtu3HfffXjooYfw4IMP4sEHHwxt47ou3vve9+Kxxx7D5cuX8brXvQ733HMP7rzz\nTgDA1atX8eijj+IVr3iF0WN+6EMfCoXTJ5OJsihi24QuD9I2+qUPK920BjnNknVaQxHIY5AoejAe\nj0OLuvM8Zl2UjvjmP1wP/i1K3YP/nt/bZYflzRwxVUpLR8bjMYClqIlp1KgpFbS/PBoZ50kdrkd1\nijIWQeUjdJ/97Gdx7733AgDuvfdefOYzn1nZ5oknnsDtt9+O2267Da1WC+985zvxyCOPBD//qZ/6\nKXzoQx8yfkx5bYSuyrUOv0BJENegJIHC5uPxGMPhMChE6Pf76Pf7IZmjSBwNtfc8L0ihUCSOInaT\nyQTHx8cYDofwPA+dTgc7Ozvo9/ulbxoqRg/OnDkDy7IwHo9xfHyM8Xic2zd9kyidCoraXdjbAcUW\nTgAAIABJREFUy3wMTH5wJC4dVAh1cnISjAbr9/vY2dkJUnv0s+l0GhRfiV+0KPrvOE4oU0DVm/1+\nH+fPn8fZs2dh2zZGoxEODg6CaOA6rhdl/swzgcd+RVP5CN3169dx6dIlAMClS5dw/fr1lW2eeeYZ\nvPzlLw/+f+XKFTz++OMAgEceeQRXrlzBd37nd6Y+BpXQEXUIcxdB0ka/qmkNqka/FIkreuTWOhHb\nJ5DMihV7JLx5P0cxOqdjNpvhwt5eUDxi2ueOyQ+Wt3SoipNUkXvVCDJVj0l5SkUejYzzfr5V/hwE\noG1ZwiyohNDdfffduKa4UDzwwAOh/+tCsbo3wHg8xgc/+EE8+uijwW1pviWdO3cOR0dHRo9Zd6K6\nqefR6FeWOPqAnc1mQWqkDhKnQ7WoW+6Sn7S6btHCJHybicwBwGAwCP0/TRNjJjkscemQPzOSFEKp\nekzO53OcnJys/P4lkbuoRsYkd3lU2tdB6HjsVzSVEDpRuGQuXbqEa9eu4ZZbbsFzzz2Hixcvrmxz\n+fJlXL16Nfj/1atXceXKFXz961/HU089hde85jUAgKeffhqvfe1r8cQTTyj3o6PRaCgrWuswKiYp\ncqo5TaPfuGkNKokbDAZb1Y9I7rWlG4G0ydYJLHf5whKXDvEzw6Q5uAni75hqSoU8goyOI2kjYxpm\nT/vL0si4DteiOjyHIqmE0EVxzz334OGHH8b999+Phx9+GG9/+9tXtrnrrrvw5JNP4qmnnsLLXvYy\nfOITn8DHP/5x3HnnnaEU7bd8y7fgz//8z7GXYl2QLjK4bevo0jT6Fac1iN9ao6Y1NJvN0MitbSZq\nBJLp6DExSmcanXv4gUvGx0gywmKXjDODQXD+GHNEeaL+cFklTofu9280GiWaUiE2MZaH2VOfuyyN\njOsgQ7yGLprKC9373/9+vOMd78BHPvIR3HbbbfjkJz8JAHj22Wfxnve8B5///OfRbDbx4Q9/GG97\n29vgui7e9a53BRWuInm/KbZF6MReTfThQ+tRTBr96qY10IdxlmkN24bq4uI4jnauLJ23RUpoEL3z\nHOCoXTz0GsUNn+eLWBj6HCL5EaP36/riJ/7+ielWkxFk9PkpT6mwLCskdxS5G4/HiRoZ11nomAU8\nKSIn3vKWt+D3f//3Q9+kxRFPdUPX6Nd1XWVEIe20Bnr9WOKyoUpVUzWwOIbs3/z888b7TBKhi2Pb\n5S4unSpHnFjuloivC7UEKePrIh+nbkqFuPSEpE5cO0yIjYwdx4ltZDwajYI+nlVF9xzW3T+0rFQ+\nQlcWdnd3cXh4iJtuuim4rW5vMPGbJFWcNptN9Hq94MNmMpkAUFem6qY1qEZuiftksiNeKACU7rXd\nxshdkjVxUWn1bZQ7cY1ZVSra5QII3ZQK2k5eviJ+CabzTPfr9/vBFzZquyJG7ihbVLbf+6TQ/FZG\nDQtdTuzu7mJ/f39F6KoeAE3T6JcidgCUjX7FtAhVu65j5Na2IcoyRU7ltgxiVJQaqZqQZ3ROJonc\nWZrfL7/E76OsxQ3bKnfi+5kiy2WXOB26JuKj0SgUMY+SO/osluVObmQMAK1WK2gPVWU45RoNC11O\n1Km5sK5HXNy0BmDxnGktiDjcXpS4Mk9rqDomEidCo3OozxYwWf9BR6CTO53IqX5uIneW7xcqgUVV\nqNZd7uRlGHHv5yoiyx1F2sQlO6rIXdSUCnpP9Pv90DpaahlF74uqvYZcFBENC11OUIROhNYoVYE0\njX7F5yamAiiqRzNJiTp+GJeBpBKnw7IsPPzAJdz7c2ZVrutGlKJrzz1nfD+d3MlSmFQC41h3m5G6\nyJ1qLe22RPDFIgc5ei6uKRbljj6LRblTNTKezWZBYcU6GhkXgUroqnDc64KFLieipkWUlaSNfk2n\nNYgLf+kCIpbo0+38i5geVfppXbL8Gz+3g/l8vtFU1y233hr8O63cmW6XRO7K0iuuanKXpeFvXZGj\n5/T6TCaT0Ngx0ykV1B6F3hNFNzIuAk65RsNClxN7e3uh5sVAOVOueTT61U1rEFOtqrUt8jdOcSEw\n/5LGs0mJE2k0GphMJsECZV1V3bpIK3emxMldWSROR1nljr4AOo6TW8PfuqKaUiGOIBMjd2JLIvrM\nEPt9ep63lkbGRaAa/cXXjiUsdDmxu7uLv/mbvwndVgahS9voVyVx4kJ61bSGfr8feVEQv3GKC4FF\nuaviAuciKYvEidB6H9Vc2U2fw3XInW9ZpZc4HZuWO1X7lXa7zRKXAFnudOcQQCDM1CaFsjGqKRVx\njYw3LXfiNYlRw0KXE2UqitD1iItq9CtKXNS0BhK5rE07xQ8QWQzSdEGvE/R6UBR13WsPTdfRiW0Y\nxHMIoBQpvbzlTtxfHZDlTjcbOOs5FNOAjuNspOFvXZHP4Xw+x3Q6xXQ6BbBckyemUeOmVOTVyDhv\nKN3KQqeHhS4nNi10Oomjb74qiZOnNZiM3Crig1geOE9hf/r2XuY1HXmhWnvY7XZLF7HUtSuJOodl\nmCtLMub7Pq4n6HNXN4nTIfY4E1tpjEYjAOkEXfWe3raZy+tAbDBMRSS9Xg+WZYUqXNNOqZDX8TmO\ng6Ojo9hGxkU8T65wjYaFLif29va0RRFFLeQ0afQrQhInftNRSRx9MKx75BYdT6/XU46tarfbQRuU\nOqC64FW1rxahOody1GfdqRt5icCZnZ3g4vb89dVI5LZInI4scicvEajDe7qMqNYfttvtlSISiu6r\nRpBRZE+UO3GEozylImkj4yKeM7+HomGhy4lz587h8PAwdFvREmfa6DduWoO4ZkJsE7DJdS1iKkG8\nIIu9mapYKVtHidOhW691cnKinCubJ3Kxjm7B/bbLWxxxcke/i3Ruy7LOs46oZtWarD8UzyH9HlJq\nNq7XXZZGxvQFPK/3AEfo4mGhywndLxSlXbOuQUnb6BfQT2uoSq8neRFwlSplxfVDVZK4vPvRqdb6\niFV6ecgdV00WiygG7XY7mCHqOA4ABNmBsv4uVhVR4miNcZZlLypBNxlBpmpkTHKnamQ8Go3geV6Q\nls36BVxV4cqEYaErmLTr6LI2+qVfOFnixJFb9C2qjBKnowqVslWVuDjyGvela8EwmUwSR1/lqkmW\nuOJQrdX6/9u787Amz3R/4N9A2MFdaAVbFxSw7opomaKlRREV2YREFvdlrqFq58yp45zOaZ0ZazvH\n9pxe2vbY6ZxKQJIgi6BsFhWqVcGtaqd1pShQRRGkgEBIyO+P/t40CW8gYEjyJvfnr6Jv2yfr++V5\n7ud+HB0dVbPozGtoLjueucxYS9dsR5AxYaynI8j0aWSsPnNniEbGus6ipffXryjQmZH+NPrVdVoD\ng5kyt8TlEHPaKWupIW6gsYU7ZkedrnDH1vrCzs4Orq6uFOIMTLv+kJmdY6vT1Z71Mad2Nlxg6mPO\n+nMEmfoycG/h7lkbGVMNXe8o0BkQn89HZ2enqgcQ0PsMXV8b/fb3tAZLCXG6mGKnLIU4w+ppaZ2Z\noWb+nFpfDJxnmfXUVXNH4Y6duZ6QwXYEmVwuV30W1Usk9DmloqdGxuqzgT1tmKIaut5RoDMgpnXJ\nyJEjVX+mHegM2ei3txBnjcFioHfKqj/XTHsYS32uTXmuKxPYmBodpogbgOo3e0v+BcXYBmLWk8Id\nO66VCbC1LtFV/8p2SgXAHu762shY15Ir+RUFOgPSFejUA1x/Gv2qhzj1nanapzUwRcnW9gWpi6F2\nyuq62fV2MoYlMVT9XG+0Zz0BaPQvY2YL2HboWcPrYGjq72sAAzbrSeHOeM/1QNJV/8rU06m/jj01\nMlYPdzyefo2Macm1dxToDEi9ubD6TByzrGqIRr9sR25Rs87e9XWnrK4QR8+14bEtXTObdbSfa/Uv\nf3PdFGPutHdNGvuXE2sKd5bcl0/7O7WnY+S0Gxkz772+NDJmJji074tcfx4NiQKdAQ0ePBgVFRU4\ncOAAZsyYgZUrV6pmiRwdHbtdzxbi1KemAfbTGvh8Pud+szMnunbKMrUcAFR1ihTiBs6zlgmw7dCz\nxFBgCOYaLCwx3Jl6c4MpaLcl0g53zEx6X0+pUG9kzPR51W5k7ODgYLLHbW54SmOdTWWhnj59iuLi\nYmRnZyM7OxsTJ05EZGQkIiMjMWbMGFWLECbQ6ZqJ0270q72zbCCbsFoz7Zk49T831ZmFlowtxBn6\nhs32/2DqcSz1hsqGWRmQyWSqNkVcWp42xnvFUHRtbnjW3mtcp2vjmPbrqN4Ohe2UCgB48uQJ3Nzc\nYGNjo6qN7urqwvDhw035EM2KxQS6hoYGxMXF4e7duxgzZgwyMjIwZMiQbtcVFRVh27ZtUCgUWL9+\nPbZv3676u7179+LTTz+Fra0tlixZgg8++KDH/+eePXvw17/+Ff7+/oiKioKtrS1aWlqwceNG1TXq\nH3DmzasrxKn/VkchbuDoWk5lvmR0dWSn16J/2Jb4jHFj1lWPZ8x2NsbGNjvEpRCnizmGO12bG+h7\nQjft15GtBlY73DG1dq2trRg8eLDGc8s85+QXFhPo3nrrLYwYMQJvvfUWPvjgAzQ2NuL999/XuEah\nUMDHxwclJSXw9PSEv78/xGIx/Pz8cPLkSbz33nsoKCiAnZ0dHj16pLG5gc2dO3cwZMgQ1W8IJSUl\nKCsrwx/+8AeNNyXzYdcOBeq9ftRPa7Ck80rNRW8hrrd/T/vMRHqNesa2xGfKG3B/X38usLbZIVOH\nO+b/z/Re663dBmGn/R3BFu60fxl0dHRULdsys3gU6H5lMTV0eXl5KCsrAwCsWrUKCxYs6BboKioq\n4O3tjTFjxgAABAIBcnNz4efnh88++ww7duxQvTl6C3MAMH78eI2f7ezscPXqVVWAY27+zFFHTFNF\n9Vkgc+k7ZIl62tig703cUDtlrQHbFzTzBWzq56enGh8uzqzoavhrrq0vDEn7XFJj1NyxzTJTHfOz\nYauBZWqZmdUrpsE+8z0CQHVKRXt7OyoqKrB06VKLf8/ry2Kehbq6Onh4/NJawcPDA3V13ftn1dbW\nYvTo0aqfvby8UFtbCwC4desWvv76a8ydOxcLFizAhQsX+jyG559/Hvb29liyZAl2796NO3fuwMbG\nBnfv3sUnn3yC+vp6AFA1YWQKgrm+HGJOmCWnp0+form5Ge3t7eDxeHBxcYGbm5vGF0NfqbcrGTRo\nEOzs7NDZ2Ymff/4ZT58+VX3ZWxPmy7WlpQUtLS1QKBRwcHCAm5sbnJ2dzfK9rd7ih3lPKBQK1WPo\n6OjQOIHFXDAhrq2tDc3Nzejo6ICtrS3c3Nzg6upqlbNETLBzc3ODi4sLeDye6vlpa2tTFdz3h/Z7\nW6lUqt4zzIYSYhjqm2PUl14B4Ntvv8XBgwfR0NAApVKJs2fPYtu2bYiIiMC1a9fM8rNqKpyaoQsJ\nCcGDBw+6/fmuXbs0fubxeKw3kZ5uLHK5HI2NjTh37hzOnz+P2NhYVFZW9ml8EydOxKFDh6BQKHDg\nwAGsW7cO9+/fh1wux8KFC7F8+XIMGjRI1WyY+e2ypaVFY0nW3G6A5k59tsJYh7Lr2ilrDe0z1Gfi\nmGJ7ru7i0zUDy8ykm3rmjq2e81kb/loqQ8zcWeMOVVNSf28D3XvzMZMfeXl5+OMf/wh7e3tMmTIF\n27dvx8KFC+kzoIVTge6rr77S+XceHh548OABnnvuOdy/fx/u7u7drvH09ER1dbXq5+rqanh5eQH4\nZbYuKioKAODv7w8bGxs8fvy4zztodu3aBbFYjIaGBkRFRWHx4sV4+PAhpFIpduzYgdjYWISFhcHJ\nyUljCUj7DEvqhN8zU4Q4XczpTNmBol3vaYk3Ol1NU9vb242+vG4JTWhNqS/hzlyP37JU6s2De2qh\nU19fj6ysLOTk5OC5557D//3f/0GhUCA3NxdCoRBTpkzBb3/7WwiFQhM+GvPCqUDXk/DwcKSkpGD7\n9u1ISUlBREREt2tmz56NW7duoaqqCqNGjYJUKoVYLAYARERE4MSJE5g/fz5u3rwJmUzWr+3Qw4cP\nx+eff465c+dqBIs1a9agpqYGBw8eRHh4OHx8fCAQCPDyyy9r1PBod8K39NmevjCnEKeLKc6UHShs\nsxVMw19Lfy/21Ih6oMIdW52WOfSK4zq2cPf06VNVewym/MVaahBNgS00s/1C2N7ejsLCQkilUrS2\ntiIuLg65ubkYOnSo6pq4uDi0t7fj+PHjkMlkpng4Zstidrk2NDQgNjYW9+7d02hb8tNPP2HDhg3I\nz88HABQWFqralqxbtw47duwA8Et7kbVr1+Lbb7+Fvb09PvzwQyxYsGBAxqpUKvHtt98iJSUFZ8+e\nRXBwMAQCASZMmKBxHdt0tLXVyVhCTz4u7ZTVDnG08UOToduCmNtuYEunvUPWxsZGVYNFz71h6dvW\npaurC+fOnYNEIsF3332HsLAwJCQkYOzYsfQ69JHFBDquksvlKC4uRmpqKh48eICIiAhER0drzA6y\nfTAsud7OEkKcLubYYoJCXP/0t3Gv+pITFxv+co0+odnUrVAsCdtEhHbZiVKpRGVlJcRiMUpKSjBr\n1iysWrUKc+bM4fx3vClRoDMjTU1NyMzMhFQqhbOzM+Li4hAaGqpxtIn6+XbMzdcS6u0sOcTpYsom\nsGzvIwpx/cfWsoU5ZYSp09IOzZbwuTVXz/LZonDXd2x1cWzPWUNDA7Kzs5GTk4Nhw4YhPj4eS5Ys\noeO7DIQCnZm6e/cu0tLScPToUUyZMgUCgQABAQEaHw6lUqn6TYiLyzXWGOJ0McbSm67ZQXNc+uUy\n5rVkbm7Msh7TK45C88AYiNlvCne6sT3fbL+kdHR04NixY5BIJHjy5AlWrFiBuLg4OrJrAFCgM3NK\npRIXLlxASkoKLly4gNdffx1CoRBjx47VuI4r9XZsMxXMF6+5jdVUtG8iz7JTlkKzcWlv3GGOLWLO\nb6ZAYFjGPH6Lwl33Njo91cVdvHgRYrEYly9fxsKFC5GYmIgJEyZYzXNlChToOEQmk6GwsBBpaWl4\n/PgxIiMjERUVpbEDyBzr7XTVaNHMUM/6e6asrt3AFOIGhr6hQldQVz/TmejH1MdvWVu4096BzfZL\nplKpxN27dyGRSFBcXIypU6ciKSkJgYGB9L1jJBToOKqxsREZGRmq3bwCgQAhISGwt7dXXaNdJ2Xs\nGi0KcYbT205ZCnHGpavhrz4zqcy/qx1ILKFf4UBSf86YEMWEOFOGKEsNd9p1cdp1oYympibk5OQg\nKysLrq6uiI+PR3h4OBwdHU04eutEgc4CVFZWIjU1FYWFhZg5cyYEAgFmzZql8aEzVo0WhbiBpx3U\nmaJ7Wk4deIaeZdN13rA5lkuYgr6hwlwoFArVL1aWUNesqy6us7MTJSUlkEgkePjwIaKjoyEUCvU6\nA50MHAp0FkSpVOLcuXNISUnBlStXsGjRIggEArzwwgsa17F1oe/vDYRaXhgXWwBgZuioBcbAYJsZ\nGoibtDHrwcyZpezk50qPwb7UxV25cgXp6em4cOECgoODkZSUBF9fX7N6PNaMAp2F6ujowNGjR5GW\nlobm5mbExMQgIiICgwYNUl3T33o77WOgKMQNLF2zONpLdFy5gXBBb21IBpq1LaHrKimwlO8UU7+f\nehoT84uKrrq42tpaSKVSFBQUwM/PD4mJiQgKCqLyADNEgc4KPH78GBKJBJmZmRg5ciSEQiFee+01\n8Pm/nvzWW70dhTjj0jfE6WLInbLWwpR9AXsblyW2m+nvph+uYwt3xq5t7m0Ju7m5Gbm5ucjMzIS9\nvT1WrlyJ5cuXw8XFZUDHR54NBTorc/PmTYhEIpSUlMDf3x9CoRDTpk1jrbdjPvRMjRaFuIH1LIX2\nfflvWsNNU19cKxmwhIbQ+uyYtBbGCHf61sXJ5XKcPHkSYrEYtbW1iIiIQHx8PDw8PDjz3rJ2FOis\nVFdXF06fPg2RSIQffvgBixcvRlxcHPh8PnJzc9HU1ISNGzeqZvHUl32oYNtw1Hc8ah+VY+jde1w6\nU3YgmePxa/3BpTBK5QC9M3S4Yz7rPdXFKZVKfPfdd0hPT8fZs2cxf/58JCUlYfLkyfS6cBAFOi1r\n165Ffn4+3N3dce3aNdZrtmzZgsLCQjg7O+PAgQOYMWOGkUdpWFVVVfjb3/6G3NxctLW1ITAwEElJ\nSYiIiFB9qM2xvx2XsbU6MGYLBksJNfpiC7OWVJNmjsvF5jgmruhvuNO3Lq6urg5SqRRHjhzB+PHj\nkZSUhODgYM7OklZXVyMpKQkPHz4Ej8fDxo0bsWXLlm7XWdq9WxsFOi2nTp2Cq6srkpKSWANdQUEB\n9u3bh4KCApSXl2Pr1q04d+6cCUb67M6dO4cdO3bg8uXLCAsLw4oVKzBjxgzk5uYiOzsbnp6eEAqF\nWLBgQbcvBFP1t+Myc+1XZak3XrY6RGtYbjZ1jZY1/aJgDL29nuqfX4VCobMurrW1FXl5eTh06BB4\nPB6EQiEiIyPh5uZmwkdnGA8ePMCDBw8wffp0tLS0YNasWTh8+DD8/PxU11jSvVsXCnQsqqqqsGzZ\nMtZAt3nzZrz66quIi4sDAPj6+qKsrAweHh7GHuYzu3PnDr777jssWrSItQnk999/D5FIhJMnT+Ll\nl1+GUCjE5MmTNa5hW0oxh2af5sJcQ5wuXF8ao6a9mozVf5LarRhHX+ubFQoFTp06hfT0dPz4448I\nDw9HfHw8PD09OfF57q+IiAi88cYbeO2111R/Zkn3bl34vV9C1NXW1mL06NGqn728vFBTU8PJN8X4\n8eMxfvx4nX8/adIkvP/+++jq6kJpaSk+/fRT3L59G8uWLUNsbCw8PDxgY2MDBwcHODg4qL7UW1tb\nrWY2hA3bTdTJyYkToYjt9WxrazP74nW24Ozi4mL1v1iov57M+5J5PZ813LEdv+Xi4mKW7w9LwfzC\nolQqYWNjAxsbG1UHgnfeeQfBwcEIDg7Gjz/+CLFYjK+//hqBgYH4t3/7N0yfPt0qPgtVVVW4fPky\nAgICNP7cku7dulCg6wftSU1L/5DY2NiovihaW1tx+PBhJCcnQ6lUYsWKFVi2bBmcnZ1ha2sLW1tb\nVRiQyWTo6Oiwino7thDn6OjIiRCni/rryexMNKewzuXgbAo9hXV9Z9bZmixTcB5YbHVx2sG5ra0N\n7u7u+Nvf/obVq1fD3d0dq1evRmlpKZydnU04euNqaWlBTEwMPv74Y7i6unb7e0u/d1Og6yNPT09U\nV1erfq6pqYGnp6cJR2RcLi4uiI+PR3x8PO7fv4+DBw8iMjISY8eOhUAgQFBQEGxsbMDn88Hn8zXq\n7dra2iymPgtgr21xcHCwiMemjsfjwdbWFk5OTnB0dGQN68baKWstz/lA0w7rnZ2dePr0KQB0W6JW\n713GnEZCwXlgsdW1sj3nbW1tOHr0KDIyMtDZ2Yk33ngDAQEBKCkpwaFDh/Dxxx8jPDwce/bswfDh\nw034iAZeZ2cnoqOjkZCQgIiIiG5/bw33bqqhY9FTDZ16YeW5c+ewbds2iyus7I+rV69CJBLh1KlT\nCAoKgkAg0ChIBSyj3s6UBefmxlgF8Ja6acPcqNfCMcuoTFNxrh6/xSXqO7F7+jwpFAqcPXsW6enp\nuHHjBpYuXYqEhAS88MIL3V6bmpoa5OTkYPPmzbCzszP2QzIapVKJVatWYfjw4fjv//5v1mus4d5N\ngU6LUChEWVkZ6uvr4eHhgZ07d6r6g23atAkAkJycjKKiIri4uODLL7/EzJkzTTlks6JQKFBSUoLU\n1FTcu3cPy5cvR3R0NNzd3btdp37jMIclPF2YGhX1GQoKFJoMHbosoYEu12gHCuYXLYVCoVE2YY6f\nUS5Tf851fRcqlUrcunULEokEJ06cwNy5c5GQkIDZs2fT6wHg9OnTCAoKwtSpU1XfD++99x7u3bsH\nwHru3RToyIBpbm5GdnY2xGIx7OzsEBsbiyVLlmjsqNXuD2Zra2sWN26aFeq//u6s1J7xs7W1tcrG\nx8akz0kitIvV8PTpFwcA9fX1yMrKwuHDh+Hh4YGEhASEhobC3t7eRCMn5owCHTGKmpoapKWl4ciR\nI/Dx8YFQKMS8efO6/RZqyhDFpc77XNHbmbIUFkyjv8dvsYVuer30w/b9xtYvrr29HUVFRZBKpWhp\naUFsbCxiY2MxdOhQE46ecAEFOmJUSqUSly9fhkgkwtmzZ/Haa69BIBDA29tb4zpd9XaGbolAIc44\n1GeCmGV2puUC0/KCjpQbWIbuSUdNhHunb11cV1cXysvLIZFIcO3aNSxevBgJCQkYN24cPZdEbxTo\niMl0dnbi2LFjSE1NxYMHDxAZGYmoqKhuu7EMXW9HIc401F9HAKqCe1paHTjGmvWmz5Qmfb6zlEol\nKisrIZFI8NVXX2HmzJlYtWoVAgIC6HNA+oUCHTELTU1NyMzMhEQigYuLC+Li4hAaGgoHBwfVNfr+\ntsuGZhNMQ3tpT3tnM70uhmfq59TUpROmwtajj21VoaGhAdnZ2cjJycHQoUORkJCAJUuWaHzXEdIf\nFOiI2amqqkJaWhry8/MxZcoUCIVCzJkzR+NmoM9Ng4rsTeNZNkVYYxAwBHOtRbT0HeL61sXJZDIc\nO3YMEokEjY2NiImJgUAgsPjecMS4KNARs6VUKnH+/HmIRCJcuHABISEhEAgEGDt2rMZ12ucb8vm/\n9Mtm2i2Yw43N0hn6xs31M2WNRT3EAd2bApsTS+nh2Je6uIsXL0IikeDSpUtYuHAhEhMTMWHCBE49\nXsIdFOgIJ8hkMhQWFiI1NRUNDQ2IiopCZGQkhg4dCplMhhMnTmDixIkYPny4aimPx+PBwcGBwtwA\nYaubGojms73tlLU2lhB2ufgY9K2Lu3fvHiQSCYqLizF58mSsWrUKgYGB9B1EBhwFOo4rKirCtm3b\noFAosH79emzfvl3j7+vr65GQkIAHDx5ALpfjD3/4A1avXm2awRpIY2Mj0tPT8cUXX0AaIPizAAAc\n6UlEQVQul+Onn37CmDFj8F//9V+YM2cObGxsnqnejuhmyvosfXqmWSpLXo7WDuzmFO703W3f1NSE\nnJwcZGVlqY5HDA8Ph5OTk4lGTqwRBToOUygU8PHxQUlJCTw9PeHv7w+xWKxx5Na7776Ljo4O7N69\nG/X19fDx8UFdXZ1qWZJrTp06BbFYjKysLIwePRqvv/46bGxscOLECcyaNQsCgQAzZ87std6Orc6F\nsFMPcXK53Ojnt+oak3pDanMYk6GZenODKeiajTXm8YD6hufOzk4cP34cYrEYdXV1iI6OhlAoxMiR\nIy329SHmjZt3dQIAqKiogLe3N8aMGQMAEAgEyM3N1Qh0zz//PK5evQoA+PnnnzF8+HDOhjkAqiB3\n5swZjB8/XvXnSqUSZ8+eRUpKCt566y2EhoYiLi5Odb6hvb097O3tVb9xt7W19bgTzdrpKrJ3dHQ0\ni8DE4/HA5/PB5/M1gk9bWxungw9bUDWn532g2drawtbWFg4ODqrPamtrq6pX4UAttes6scbZ2blb\nXdyVK1cgFotRUVGB1157DTt37oSfnx/n3mvE8tAMHYdlZmaiuLgY//jHPwAAaWlpKC8vx969e1XX\ndHV1ITg4GDdv3kRzczMyMjKwePFiUw3ZKDo6OnD06FGkpaWhpaUF0dHRiIiIwKBBgzSu49J5ssbA\ntqRpzkX2bLi6NKl9nic1Wv6V9i8Xhnxf6lsXV1tbC6lUioKCAvj6+iIpKQlBQUGc+VwQ68DdqRqi\n1w3qvffew/Tp01FaWoo7d+4gJCQEV65cgZubmxFGaBoODg6Ijo5GdHQ06uvrIZFIIBAI4O7ujpUr\nVyI4OBh8Pl9jNoC5oba3t3N6hqc/2HZKuri4cPJmxTYb29HRgba2NrOqzQLYj9/i6vM+kNRnYx0d\nHVXv19bW1n7tYmeri2N73pubm5Gbm4vMzEzY2dlh5cqVKCkpgYuLy0A8TEKeGQU6DvP09ER1dbXq\n5+rqanh5eWlcc+bMGfzHf/wHAGD8+PEYO3Ysbty4gdmzZxt1rKYyYsQIJCcnIzk5GTdu3EBqaip2\n796NgIAACIVCTJ06tdvyHfNlz4QAS6y3Y2uC6uTkZFGP08bGBg4ODqrArr7UbqqdsmxhwtKe94HE\nFu5kMhk6Ojp6DHdsM7cODg7dZm7lcjlKS0uRnp6O2tpaREREICUlBc8995xFvD5r165Ffn4+3N3d\nce3atW5/X1paiuXLl2PcuHEAgOjoaLz99tvGHibpJ1py5TC5XA4fHx8cP34co0aNwpw5c7ptivj9\n73+PwYMH45133kFdXR1mzZqFq1evYtiwYSYcuWl1dXXh9OnTSElJwfXr1xEWFoa4uDiMGjWq23Xq\noYfr7TK42CrC0EyxU5ary8BcwtZEnJlhl8vlGnVx2jPvSqUS3333HcRiMc6cOYOgoCAkJSVhypQp\nFvf6nDp1Cq6urkhKStIZ6D766CPk5eWZYHTkWdEMHYfx+Xzs27cPixYtgkKhwLp16+Dn54f9+/cD\nADZt2oQ//elPWLNmDaZNm4auri78/e9/t+owB/wycxMUFISgoCC0tbUhNzcXb775JmQyGVasWIHw\n8HC4urp2m+GRyWSqAm2u1NsxYUK94S/bzIS14PF4sLW1hZOTE+sMj6F2yuraoapdZE8MQ72uTi6X\no6OjA+3t7QB++bzb2tqis7NTtVyqVCpRV1cHqVSKI0eOYNy4cUhKSsKePXs4vWmsN6+88gqqqqp6\nvIbmeLiLZugI+f/q6uogFouRnZ0NLy8vCIVCLFiwQGNGjgv97YzV8NeSGKJFiLkev2UNdPWLY2bo\nLl68iMjISPzmN7+Bj48Prl27Bj6fD6FQiKioKIuuKdZWVVWFZcuWsc7QlZWVISoqCl5eXvD09MSe\nPXswadIkE4yS9AcFOkJYfP/99xCJRDh58iQCAwMhEAgwefJkjWvMqb+dNfYsGyh9XSLl0vFbloR5\nzzOtRnS9TgqFQtW/8smTJ6isrER1dTXCwsIgEAgQGhoKR0dHEz4S4+op0DU3N8PW1hbOzs4oLCzE\n1q1bcfPmTROMkvQHBTpCeqBQKFBWVoaUlBRUVlZi6dKliI2NhYeHh8Z1pqi309WzjGaEDEdX3SEz\n82PN9YimoKuhNFtd3PXr1yEWi/H111/j5ZdfRlJSEmbMmAEej4f6+npkZWVBKpXi4cOHuHbtmtW8\nbj0FOm1jx47FxYsXrb5Mhyso0BGip9bWVuTk5CA9PR0AEBsbi6VLl8LZ2VnjOvUlWUOHLFrWMx2m\nNksulwOAKkwwS3tk4OjbL+7Ro0c4dOgQcnNzMXr0aCQkJGDhwoWws7PT+d9++vRpt8+wJesp0NXV\n1cHd3R08Hg8VFRWIjY3tteaOmA8KdIT0w/3793Hw4EEcPnwY48aNg1AoxCuvvNLtBmOIZVBLaPjL\nVbpeQxsbG41Gt1zZJMMluuritI8Ba2trQ35+PqRSKWQyGQQCAWJiYjB48GATjt48CYVClJWVob6+\nHh4eHti5c6eqVGDTpk345JNP8Nlnn4HP58PZ2RkfffQR5s6da+JRE31RoCPkGV25cgUikQinT5/G\n/PnzIRAI4Ovrq3GNel2WQqFQbVToaYnOHM61tEZ9mQW1hjNljUnfuriuri6cOXMGYrEY169fx5Il\nS5CQkIAXX3yRPhvEalGgI8RA5HI5SkpKkJqaipqaGoSHhyM6Ohru7u4a1/VUb8fW8Jdqs4xDe1mv\nr8dv0caU/mEL0Lrq4m7dugWJRIITJ04gICAACQkJ8Pf3p/BMCCjQETIgmpubkZWVBYlEAjs7O8TF\nxSEsLKzbbjqFQoGOjg7VsgcAiz2dwhyxBWi2Zb2+ombCvWPbHcwWoJkNDDk5OfDw8EBCQgIWL14M\ne3t7UwybELNFgY6QAVZTU4O0tDTk5eXB19cXQqEQvr6+OHLkCI4dO4a9e/fC0dERNjY26Orqot5x\nA0y92XJXV5dey9/Pgk7o+JW+dXHt7e0oKiqCRCJBa2srYmNjERsbi6FDh5pw9ISYNwp0xOiKioqw\nbds2KBQKrF+/Htu3b+92TWlpKd588010dnZixIgRKC0tNf5ADay1tRX79u3D559/jp9++gmzZ89G\nVFQU1qxZozHbYOzAYQ20a7NMFZh11UVa8uaWvtTFlZeXQyKR4Nq1awgNDUViYiLGjRtH73tC9ECB\njhiVQqGAj48PSkpK4OnpCX9//27nzz558gSBgYEoLi6Gl5cX6uvrMWLECBOO+tnU19dj69atyM/P\nR0BAAAQCAZYuXYry8nKkpqairq4OkZGRiIqKwvDhwzX+XUs7T9aYtE/1sLW1Za3NMtXYjH2mrDH1\npS6usrISEokEX331FWbOnImkpCTMnTvXIp4HQoyJAh0xqrNnz2Lnzp0oKioCALz//vsAgD/+8Y+q\naz799FM8ePAAf/nLX0wyRkOTy+X44osvEBUV1W2DBAA0NTXh0KFDkEqlcHFxgUAgwKJFi+Dg4KC6\nRjsAUP85dlwMSpa0U1bfurjGxkZkZ2cjOzsbQ4cORXx8PJYuXarxnieE9I3lnkJMzFJtbS1Gjx6t\n+tnLywvl5eUa19y6dQudnZ149dVX0dzcjK1btyIxMdHYQzUYPp+PzZs36/z7wYMHY/369Vi/fj2q\nqqqQmpqKjz/+GFOnToVAIMCcOXO6HSrP7KZsb2+nejuwL2W6uLhwYiaTx+OBz+eDz+dr7JRta2vj\nxE5Ztro4JyenbiUCMpkMx44dg0QiQUNDA1asWIFDhw5xevadEHNCgY4YlT43pc7OTly6dAnHjx/H\n06dPMW/ePMydOxcTJkwwwghNa8yYMfjzn/+Mt99+GxUVFRCJRPjTn/6E119/HQKBAGPHjtVoLMzU\n23V0dKgCgLXU2+kbJLiE7bVlwp057ZRlq4tzcHBgrYu7ePEiJBIJLl26hJCQEOzevRsTJ040+WMg\nxNJQoCNG5enpierqatXP1dXV8PLy0rhm9OjRGDFiBJycnODk5ISgoCBcuXLFKgIdg8fjISAgAAEB\nAZDJZCgoKMA777yDhoYGREVFISoqCkOGDFEtKdrb26uWGtva2iy23o6tHQhbkLAE2q+tenA3xU5Z\nXXVxzs7O3eri7t27B4lEgqKiIkyZMgVJSUn45JNPOLeETAiXUA0dMSq5XA4fHx8cP34co0aNwpw5\nc7ptirh+/TqSk5NRXFyMjo4OBAQEQCqVYtKkSSYcuXlobGyEVCpFRkYGhg0bBoFAgJCQEI2zKi2t\n3o4a9moy9k5Z9fcSoLsurqmpCYcPH0ZWVhacnZ0RHx+PZcuWWdU5qYSYEgU6YnSFhYWqtiXr1q3D\njh07sH//fgC/nCcIAHv27MGXX34JGxsbbNiwAVu2bDHlkM3S7du3kZqaiuLiYsyaNQsCgQAzZ87s\nNluiHYa4UG/Xl+O3rNVAbgBRKpWq/25PvfM6Oztx/PhxSCQSPHjwANHR0RAKhRg5cqRZv78IsUQU\n6AjhOKVSiTNnzkAkEuHq1asIDQ2FQCDQ2HzCXKfe384cG9w+6/Fb1soQO2X17dXX1dWFq1evIj09\nHRUVFQgODkZSUhL8/PzM5n3UX2vXrkV+fj7c3d1x7do11mu2bNmCwsJCODs748CBA5gxY4aRR0kI\nOwp0hFiQ9vZ2HD16FGlpaWhtbUVMTAyWL1+OQYMGaVzHtoxmqnq7gTp+y1r1ZYm6L/3iamtrkZGR\ngfz8fPj6+iIxMRHz58+3qBrNU6dOwdXVFUlJSayBrqCgAPv27UNBQQHKy8uxdetWnDt3zgQjJaQ7\nCnSEWKj6+npIJBJkZmbCw8MDQqEQwcHB4PN/3QtlqqVN9dlChUJB59cOEF1nytrY2OjVL665uRl5\neXk4dOgQ7OzssHLlSkRERMDFxcUUD8coqqqqsGzZMtZAt3nzZrz66quIi4sDAPj6+qKsrAweHh7G\nHiYh3dAuV0Is1IgRI5CcnIzk5GTcuHEDIpEIu3fvRkBAAIRCIaZOnarRA22g+9uxLelZ6g5Vc6G+\nU1ahUKC9vR1Pnz4FAI3wrj7LJpfLUVpaCrFYjJqaGixfvhwpKSl47rnnrP51YuujWVNTQ4GOmAUK\ndIRYAR8fH+zatQt//etfcerUKXzxxRe4fv06wsLCEBcXh1GjRvXY366/9Xa6aru0W12QgcEWopnn\nXi6X4/z589i4cSOio6Mxb948fPPNNzhz5gyCgoKwY8cOTJkyhV4nLdqLWvT8EHNBgY4QK2JjY4P5\n8+dj/vz5aGtrQ25uLt58803IZDKsWLEC4eHhcHV11dnfDui93k7X7ktHR0fa3GAEupbRtUO0ra0t\nvL29kZSUhPLycnzxxRcYOXIkNmzYgPj4+G6bakj3Ppo1NTXw9PQ04YgI+RV9uxJipZycnCAQCHDk\nyBGIRCI0NzcjJiYGGzZswPHjx6FQKAD8EgIdHR3h6uoKJycnKJVKtLa2oqWlBR0dHejq6gLwy+aG\n9vZ2tLS0oLW1FTweDy4uLnBzc4ODgwOFuQGm/vy3tbWBx+PB1dUVrq6ucHBwUIW51tZWSCQSxMTE\n4He/+x28vb2RlZWFJ0+e4J///CcqKysxffp0LF26tNtslLULDw+HSCQCAJw7dw5Dhgyh5VZiNmhT\nBCFEw7/+9S+IRCKUlpYiMDAQQqEQL730ksY12kt5DNrcYFz6tqJRKBQ4ffo00tPTcefOHYSHhyM+\nPh5eXl6sr1NHRwf+9a9/YebMmcZ8OCYnFApRVlaG+vp6eHh4YOfOnaqNI0yPzOTkZBQVFcHFxQVf\nfvml1T1HxHxRoCOEsFIoFCgtLYVIJEJlZSWWLVuGFStWwMXFBXl5ebhx4wZ+//vfq3qdyeVyVdsR\nc+tvZ0n0bRatVCpx48YNiMVilJWV4eWXX0ZiYmK35tOEEMtAgY4QPRQVFalOt1i/fj22b9/Oet35\n8+cxb948ZGRkICoqysijHDhNTU3YtWsXDh48iKamJkyfPh0JCQlITEzs1nRWn2OiSN/o215GqVTi\n0aNHyMzMRG5uLjw9PZGYmIiFCxdqHA9HCLE8FOgI6YVCoYCPjw9KSkrg6ekJf3//bufPMteFhITA\n2dkZa9asQXR0tIlGbDh3797Fhx9+CKlUirFjxyI+Ph5BQUE4duwYcnNzMX78eAgEArzyyivdgoU+\nDWtJz/RtAN3W1ob8/HxkZGSgo6MDAoEAMTExGDx4sCmGTQgxAdrlSkgvKioq4O3tjTFjxgAABAIB\ncnNzuwW6vXv3IiYmBufPnzfBKAeGXC7HiBEj8M0338Db21v159OmTcO///u/48qVKxCJRHj33Xcx\nf/58CAQC+Pr6sva3Y3bKcuU8WVNhq4tzcnLqtoTd1dWFs2fPIj09HdevX8eSJUuwb98+vPjii/S8\nEmKFKNAR0gu2ZqLl5eXdrsnNzcWJEydw/vx5i7mhjh8/Hv/5n/+p8++nTZuGDz/8EHK5HCUlJfjw\nww9VzWijo6NVh7Qbur+dpWGri2NruqxUKnH79m1IJBIcP34cAQEB2Lx5M/z9/WlZmxArR4GOkF7o\nEzS2bduG999/HzweD0ql0uraPfD5fISGhiI0NBTNzc3IysrCxo0b4eDggNjYWISFhcHR0bHX/nbW\nVG+n3a+PqYtj69f3+PFjZGZm4vDhw3B3d0dCQgJ27twJe3t7E42eEGJuKNAR0gvtZqLV1dXw8vLS\nuObixYsQCAQAfjlDtbCwEHZ2dggPDzfqWM2Bm5sbVq9ejdWrV6O6uhppaWlYunQp/Pz8IBQKMW/e\nPPB4PFV/OwcHB1W9XUtLi8XX26mHOKVSCXt7e7i4uHSri+vo6EBRUREkEgmam5sRGxuLnJwcDBs2\nzEQjJ4SYM9oUQUgv5HI5fHx8cPz4cYwaNQpz5sxh3RTBWLNmDZYtW2ZRu1yflVKpxKVLlyASiVBe\nXo7g4GAIBAKNujzmOvX+dsySLNfr7fTtF9fV1YWKigqIxWJcu3YNoaGhSEhIwPjx4zn9+AkhA49m\n6AjpBZ/Px759+7Bo0SIoFAqsW7cOfn5+2L9/P4BfG44S3Xg8HmbNmoVZs2ahs7MTxcXF2LVrFx4+\nfIjIyEhERUVh2LBhGvV2XV1dnK6360td3I8//giJRIJjx45h5syZWLNmDebOnWs1y8+EkGdHM3SE\nEJNpamrCoUOHIJVK4erqiri4OCxatAgODg4a16m3QAHMt95OV12cdr84AGhsbER2djZycnIwePBg\nJCQkYOnSpd0eOyGE6IMCHSHELFRVVSE1NRUFBQWYOnUqhEIh/P39u81mmWN/O2Y2USaTqeri2PrF\nyWQyfPXVV5BIJHj8+DFiYmIgEAgwYsQIE42cEGIpKNARQsyKUqlERUUFRCIRLl68iIULF0IgEKj6\nAKpfZ8p6O+26OKa/Hltd3KVLlyCRSHDx4kWEhIQgMTEREydO5MTSMSGEGyjQEULMlkwmQ0FBAVJT\nU/HkyRNERUUhMjISQ4YM0biOmSHr7OzscdPBs+rLOar37t2DVCpFUVERXnrpJaxatQq/+c1vzG6Z\nmBBiGSjQEUI4oaGhAVKpFJmZmRg2bBji4uIQEhLS7YxSQ9fb9aUurqmpCYcPH0Z2djacnJywcuVK\nhIeHw9nZuX8PmhBC9ESBjhDCObdv30ZqaiqKi4sxa9YsCIVCzJgxw6D1dvrWxXV2duLEiRMQi8V4\n8OABoqKiIBQK4e7ublFLqkVFRdi2bRsUCgXWr1+P7du3a/x9aWkpli9fjnHjxgEAoqOj8fbbb5ti\nqIRYJQp0hBDOUiqVOHPmDEQikapvW1xcnMZRbcx1+tTbMXVxnZ2dUCgUPdbFXb16FWKxWNVXLzEx\nEZMmTbKoEMdQKBTw8fFBSUkJPD094e/v360XY2lpKT766CPk5eWZcKSEWC/qQ0cI4Swej4fAwEAE\nBgaivb0dR48exfbt29Ha2oqYmBgsX74cgwYN6rG/HZ/Ph62trWo2j8/nw87ODs7Ozt3C3k8//QSp\nVIqCggJMnDgRSUlJ+J//+Z9us3aWpqKiAt7e3qqNKQKBALm5ud2aa9P8ACGmQ4GOEGIRHB0dERMT\ng5iYGDx69AgSiQQCgQAeHh5YuXIlXn31VfD5fNjY2MDBwQGNjY0YNGiQakaOOWf2559/hoeHh+q/\n29LSgry8PGRkZMDOzg5CoRDHjh2Dq6urCR+tcdXW1mrMenp5eaG8vFzjGh6PhzNnzmDatGnw9PTE\nnj17MGnSJGMPlRCrRYGOEAvXW+3TwYMH8fe//x1KpRJubm747LPPMHXqVBON1jBGjhyJN954A2+8\n8QauX7+O1NRUvPfee5g8eTKGDBmCwsJCODo6oqSkBK6urrCxsYFCocCjR4/g7++PSZMmITAwEJWV\nlbh//z4iIiJw4MABPP/88xa5pNobfR7zzJkzUV1dDWdnZxQWFiIiIgI3b940wugIIQBA++cJsWAK\nhQLJyckoKirC999/D7FYjB9++EHjmnHjxuHrr7/G1atX8ec//xkbN2400WgHhpeXF3x9fTF48GBk\nZGTg9OnTGDduHKKiotDY2Kiqj7O1tcXjx4+RlJSEwYMHIz8/H8XFxXjhhRfw0ksvWdwmh77w9PRE\ndXW16ufq6mp4eXlpXOPm5qbazbt48WJ0dnaioaHBqOMkxJrRDB0hFkyf2qd58+ap/jkgIAA1NTXG\nHuaAOX/+PEJCQhAYGIi1a9fi8OHDcHZ2xtOnT5Gbm4tt27ZBJpNhxIgRuHv3Ll588UUkJSVhz549\n4PP5ePToEaRSKd59912sW7cON27cgJubm6kfltHNnj0bt27dQlVVFUaNGgWpVAqxWKxxTV1dnSr0\nVlRUQKlUYtiwYSYaMSHWhwIdIRZMn9ondf/85z8RFhZmjKEZxdSpU3Hjxg2NmjgAcHZ2hlAohFAo\nxP379/Hpp5/if//3f7uFtZEjRyI5ORnJycmorq62yjAHAHw+H/v27cOiRYugUCiwbt06+Pn5Yf/+\n/QCATZs2ITMzE5999hn4fD6cnZ0hkUhMPGpCrAu1LSHEgmVlZaGoqAj/+Mc/AABpaWkoLy/H3r17\nu1178uRJ/O53v8M333yDoUOHGnuohBBCngHN0BFiwfSpfQKAq1evYsOGDSgqKqIwRwghHESbIgix\nYOq1TzKZDFKpFOHh4RrX3Lt3D1FRUUhLS4O3t7eJRkoIIeRZ0AwdIRZMn9qnv/zlL2hsbMRvf/tb\nAL+cfVpRUWHKYRNCCOkjqqEjhBBCCOE4WnIlhBBCCOE4CnSEEEIIIRxHgY4QQgghhOMo0BFCCCGE\ncBwFOkIIIYQQjqNARwghhBDCcRToCCGEEEI4jgIdIYQQQgjHUaAjhBBCCOE4CnSEELNWVFQEX19f\nTJgwAR988AHrNVu2bMGECRMwbdo0XL582arHRQixThToCCFmS6FQIDk5GUVFRfj+++8hFovxww8/\naFxTUFCA27dv49atW/j8889VZ9Ja47gIIdaLAh0hxGxVVFTA29sbY8aMgZ2dHQQCAXJzczWuycvL\nw6pVqwAAAQEBePLkCerq6qxyXIQQ60WBjhBitmprazF69GjVz15eXqitre31mpqaGqscFyHEelGg\nI4SYLR6Pp9d1SqWyX/9ef5nruAgh1osCHSHEbHl6eqK6ulr1c3V1Nby8vHq8pqamBp6enlY5LkKI\n9aJARwgxW7Nnz8atW7dQVVUFmUwGqVSK8PBwjWvCw8MhEokAAOfOncOQIUPg4eFhleMihFgvvqkH\nQAghuvD5fOzbtw+LFi2CQqHAunXr4Ofnh/379wMANm3ahLCwMBQUFMDb2xsuLi748ssvrXZchBDr\nxVNqF3kQQgghhBBOoSVXQgghhBCOo0BHCCGEEMJxFOgIIYQQQjiOAh0hhBBCCMf9PwEiDwd1CEVX\nAAAAAElFTkSuQmCC\n", "text": [ "" ] } ], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": {}, "source": [ "\u00a1Ah! Las maravillas de la reutilizaci\u00f3n del c\u00f3digo! Ahora, probablemente pienses: \"Bueno, si he escrito esta peque\u00f1a funci\u00f3n tan estupenda que hace algo tan \u00fatil, pero quiero usarla una y otra vez \u00bfC\u00f3mo puedo hacer esto sin tener que copiar y pegar todo el rato? -Si tienes mucha curiosidad acerca de esto, tendr\u00e1s que aprender acerca de *packaging*. Pero esto va m\u00e1s all\u00e1 del alcance de nuestras lecciones de CFD. S\u00f3lo tienes que buscarlo en Google si realmente quieres saber c\u00f3mo ;)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "***" ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Aprender m\u00e1s" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Para obtener m\u00e1s informaci\u00f3n sobre la funci\u00f3n de la ecuaci\u00f3n de Poisson en CFD, puedes ver el **Video Lesson 11** en YouTube:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from IPython.display import YouTubeVideo\n", "YouTubeVideo('ZjfxA3qq2Lg')" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "\n", " \n", " " ], "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ "" ] } ], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "from IPython.core.display import HTML\n", "def css_styling():\n", " styles = open(\"../styles/custom.css\", \"r\").read()\n", " return HTML(styles)\n", "css_styling()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "\n", "" ], "output_type": "pyout", "prompt_number": 1, "text": [ "" ] } ], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "> (La celda de arriba establece el formato de este notebook)" ] } ], "metadata": {} } ] }